diff --git a/CHANGELOG.md b/CHANGELOG.md
index 4cd6396..fa696ed 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -4,6 +4,14 @@ All notable changes to this project will be documented here. Format follows [Kee
 
 ## [Unreleased]
 
+### Added
+- Native `anthropic` SDK support. Wraps `Anthropic.messages.create` (including `stream=True`) and `Anthropic.messages.stream(...)` context manager. Same coverage on `AsyncAnthropic` (sync + async variants).
+- `extract_anthropic_native` adapter with the full Anthropic field map: `input_tokens`, `output_tokens`, `cache_creation_input_tokens`, `cache_read_input_tokens`, `cache_creation.ephemeral_5m_input_tokens`, `cache_creation.ephemeral_1h_input_tokens`, `content[].type == "tool_use"`.
+- `anthropic` optional dependency group: `pip install 'lago-agent-sdk[anthropic]'`.
+- 19 new unit tests (adapter + wrapper) and 3 live integration tests (gated on `ANTHROPIC_API_KEY`). Total: 256 unit tests, ≥80% coverage maintained.
+- 9 captured response fixtures from the real Anthropic API (plain, tool use, 5m + 1h prompt caching, extended thinking, streaming, multi-turn).
+
+
 ## [0.1.0] — initial release
 
 ### Added
diff --git a/README.md b/README.md
index 89ad3f9..b8855c7 100644
--- a/README.md
+++ b/README.md
@@ -29,6 +29,7 @@ pip install lago-agent-sdk
 
 For Bedrock support: `pip install 'lago-agent-sdk[bedrock]'` (adds `boto3`).
 For Mistral support: `pip install 'lago-agent-sdk[mistral]'` (adds `mistralai`).
+For Anthropic native support: `pip install 'lago-agent-sdk[anthropic]'` (adds `anthropic`).
 
 ## Quickstart — Bedrock
 
@@ -52,6 +53,25 @@ sdk.flush()
 
 The wrapped client behaves identically to the original — same arguments, same return shape, same exceptions. The SDK adds an in-memory queue that batches events to Lago in the background.
 
+## Quickstart — Anthropic
+
+```python
+from anthropic import Anthropic
+from lago_agent_sdk import LagoSDK
+
+sdk = LagoSDK(api_key="...", default_subscription_id="sub_acme")
+client = sdk.wrap(Anthropic(api_key="..."))
+
+resp = client.messages.create(
+    model="claude-sonnet-4-6",
+    max_tokens=200,
+    messages=[{"role": "user", "content": "Hello"}],
+)
+sdk.flush()
+```
+
+Works with `Anthropic` and `AsyncAnthropic`. Both `messages.create(..., stream=True)` and the `messages.stream(...)` context manager are instrumented — usage is captured from the final `message_delta` event in either case.
+
 ## Quickstart — Mistral
 
 ```python
@@ -92,9 +112,9 @@ Backed by `contextvars` for safe propagation across `asyncio` tasks.
 |---|---|---|
 | AWS Bedrock | `Converse` (sync + stream) | ✓ |
 | AWS Bedrock | `InvokeModel` (sync + stream), 7 model families | ✓ |
+| Anthropic | native SDK (`messages.create` + `messages.stream`, sync + async) | ✓ |
 | Mistral | native SDK (`chat.complete` + `chat.stream`) | ✓ |
 | OpenAI | native SDK | Phase 2 |
-| Anthropic | native SDK | Phase 2 |
 | Google Gemini | native SDK | Phase 2 |
 | LiteLLM | callback bridge | Phase 4 |
 
@@ -102,16 +122,16 @@ Backed by `contextvars` for safe propagation across `asyncio` tasks.
 
 `CanonicalUsage` carries 10 numeric fields. Which ones populate depends on the provider:
 
-| Field | Lago metric code | Bedrock | Mistral native |
-|---|---|---|---|
-| input | `llm_input_tokens` | ✓ | ✓ |
-| output | `llm_output_tokens` | ✓ | ✓ |
-| cache_read | `llm_cached_input_tokens` | ✓ (Anthropic) | ✓ (when cache hits) |
-| cache_write | `llm_cache_creation_tokens` | ✓ (Anthropic) | ✗ |
-| cache_write_5m / 1h | `llm_cache_write_5m/1h_tokens` | ✓ (Anthropic InvokeModel) | ✗ |
-| reasoning | `llm_reasoning_tokens` | ✗ (folded into output) | ✗ (folded into output) |
-| tool_calls | `llm_tool_calls` | ✓ | ✓ |
-| image_input / audio_input | `llm_image/audio_input_tokens` | ✗ | ✗ |
+| Field | Lago metric code | Bedrock | Anthropic native | Mistral native |
+|---|---|---|---|---|
+| input | `llm_input_tokens` | ✓ | ✓ | ✓ |
+| output | `llm_output_tokens` | ✓ | ✓ | ✓ |
+| cache_read | `llm_cached_input_tokens` | ✓ (Anthropic) | ✓ | ✓ (when cache hits) |
+| cache_write | `llm_cache_creation_tokens` | ✓ (Anthropic) | ✓ | ✗ |
+| cache_write_5m / 1h | `llm_cache_write_5m/1h_tokens` | ✓ (Anthropic InvokeModel) | ✓ | ✗ |
+| reasoning | `llm_reasoning_tokens` | ✗ (folded into output) | ✗ (folded into output, even with extended thinking) | ✗ (folded into output) |
+| tool_calls | `llm_tool_calls` | ✓ | ✓ | ✓ |
+| image_input / audio_input | `llm_image/audio_input_tokens` | ✗ | ✗ | ✗ |
 
 Reasoning, image, and audio fields will populate when Phase 2 native OpenAI ships.
 
diff --git a/pyproject.toml b/pyproject.toml
index 8c23f42..4044de0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -37,6 +37,9 @@ dev = [
     "mypy>=1.10",
     "types-requests>=2.31",
 ]
+anthropic = [
+    "anthropic>=0.30",
+]
 
 [project.urls]
 Homepage = "https://www.getlago.com"
@@ -81,3 +84,8 @@ files = ["src/lago_agent_sdk"]
 [[tool.mypy.overrides]]
 module = ["boto3.*", "botocore.*", "mistralai.*"]
 ignore_missing_imports = true
+
+[dependency-groups]
+dev = [
+    "anthropic>=0.30",
+]
diff --git a/src/lago_agent_sdk/adapters/__init__.py b/src/lago_agent_sdk/adapters/__init__.py
index 31f94e8..217ed3d 100644
--- a/src/lago_agent_sdk/adapters/__init__.py
+++ b/src/lago_agent_sdk/adapters/__init__.py
@@ -1,8 +1,10 @@
+from .anthropic_native import extract_anthropic_native
 from .bedrock_converse import extract_bedrock_converse
 from .bedrock_invoke import extract_bedrock_invoke, pick_invoke_adapter
 from .mistral_native import extract_mistral_native
 
 __all__ = [
+    "extract_anthropic_native",
     "extract_bedrock_converse",
     "extract_bedrock_invoke",
     "pick_invoke_adapter",
diff --git a/src/lago_agent_sdk/adapters/anthropic_native.py b/src/lago_agent_sdk/adapters/anthropic_native.py
new file mode 100644
index 0000000..5943676
--- /dev/null
+++ b/src/lago_agent_sdk/adapters/anthropic_native.py
@@ -0,0 +1,91 @@
+"""Anthropic native adapter — verified against real fixtures.
+
+Field mapping:
+  usage.input_tokens                                 → input
+  usage.output_tokens                                → output
+  usage.cache_read_input_tokens                      → cache_read
+  usage.cache_creation_input_tokens                  → cache_write
+  usage.cache_creation.ephemeral_5m_input_tokens     → cache_write_5m
+  usage.cache_creation.ephemeral_1h_input_tokens     → cache_write_1h
+  count of content[].type == "tool_use"              → tool_calls
+
+Not exposed by Anthropic (folded into output_tokens):
+  reasoning_tokens — even with extended thinking enabled
+
+Unknown usage fields (service_tier, inference_geo, server_tool_use, …) land in extras.
+"""
+
+from __future__ import annotations
+
+from typing import Any, cast
+
+from ..canonical import CanonicalUsage
+
+_KNOWN_USAGE_FIELDS = {
+    "input_tokens",
+    "output_tokens",
+    "cache_read_input_tokens",
+    "cache_creation_input_tokens",
+    "cache_creation",
+}
+
+
+def _safe_dict(v: Any) -> dict[str, Any]:
+    return v if isinstance(v, dict) else {}
+
+
+def _safe_int(v: Any) -> int:
+    try:
+        return max(0, int(v or 0))
+    except (TypeError, ValueError):
+        return 0
+
+
+def _to_dict(obj: Any) -> dict[str, Any]:
+    """Best-effort pydantic-or-dict to dict (Anthropic SDK returns pydantic Message objects)."""
+    if isinstance(obj, dict):
+        return obj
+    if hasattr(obj, "model_dump"):
+        try:
+            return cast(dict[str, Any], obj.model_dump())
+        except Exception:  # noqa: BLE001
+            pass
+    return {}
+
+
+def extract_anthropic_native(response: Any, model_id: str = "") -> CanonicalUsage:
+    """Translate an Anthropic native response (Message or dict) → CanonicalUsage.
+
+    Accepts the SDK's pydantic Message object, a dict (e.g. captured fixture),
+    or a synthetic `{"usage": {...}}` blob produced by the streaming wrapper.
+    """
+    resp = _to_dict(response) if not isinstance(response, dict) else response
+
+    usage = _safe_dict(resp.get("usage"))
+    cache_creation = _safe_dict(usage.get("cache_creation"))
+
+    content = resp.get("content")
+    tool_calls = (
+        sum(1 for b in content if isinstance(b, dict) and b.get("type") == "tool_use")
+        if isinstance(content, list)
+        else 0
+    )
+
+    extras: dict[str, Any] = {}
+    for k, v in usage.items():
+        if k not in _KNOWN_USAGE_FIELDS:
+            extras[k] = v
+
+    return CanonicalUsage(
+        input=_safe_int(usage.get("input_tokens")),
+        output=_safe_int(usage.get("output_tokens")),
+        cache_read=_safe_int(usage.get("cache_read_input_tokens")),
+        cache_write=_safe_int(usage.get("cache_creation_input_tokens")),
+        cache_write_5m=_safe_int(cache_creation.get("ephemeral_5m_input_tokens")),
+        cache_write_1h=_safe_int(cache_creation.get("ephemeral_1h_input_tokens")),
+        tool_calls=tool_calls,
+        model=model_id or (resp.get("model") if isinstance(resp.get("model"), str) else "") or "",
+        provider="anthropic",
+        api="native",
+        extras=extras,
+    )
diff --git a/src/lago_agent_sdk/sdk.py b/src/lago_agent_sdk/sdk.py
index c401df5..c303e03 100644
--- a/src/lago_agent_sdk/sdk.py
+++ b/src/lago_agent_sdk/sdk.py
@@ -83,13 +83,17 @@ def wrap(
             from .wrappers.mistral import wrap_mistral_client
 
             return wrap_mistral_client(self, client, dimensions=dimensions, subscription=subscription)
+        if kind == "anthropic":
+            from .wrappers.anthropic import wrap_anthropic_client
+
+            return wrap_anthropic_client(self, client, dimensions=dimensions, subscription=subscription)
         if kind == "unknown":
             raise UnknownClientError(
                 f"Unknown client passed to wrap(): {type(client).__module__}.{type(client).__name__}. "
-                "Supported: boto3 bedrock-runtime, mistralai.client.Mistral."
+                "Supported: boto3 bedrock-runtime, mistralai.client.Mistral, anthropic.Anthropic / AsyncAnthropic."
             )
         raise UnknownClientError(
-            f"Client kind '{kind}' is not yet supported. Implemented: 'bedrock', 'mistral'."
+            f"Client kind '{kind}' is not yet supported. Implemented: 'bedrock', 'mistral', 'anthropic'."
         )
 
     # ------------------------------------------------------------------
diff --git a/src/lago_agent_sdk/wrappers/anthropic.py b/src/lago_agent_sdk/wrappers/anthropic.py
new file mode 100644
index 0000000..50da482
--- /dev/null
+++ b/src/lago_agent_sdk/wrappers/anthropic.py
@@ -0,0 +1,231 @@
+"""anthropic SDK wrapper.
+
+Wraps the public methods of `Anthropic.messages` (and `AsyncAnthropic.messages`)
+in place — instrumentation never breaks the customer's call.
+
+Methods wrapped:
+  - .create(...)                   — non-streaming and stream=True both supported
+  - .stream(...)                   — sync context-manager helper
+  - AsyncMessages.create(...)      — async non-streaming and stream=True
+  - AsyncMessages.stream(...)      — async context-manager helper
+
+Per-call override: pop `extra_lago={"subscription": ..., "dimensions": ...}` from kwargs
+before forwarding so Anthropic's strict validation doesn't reject it.
+"""
+
+from __future__ import annotations
+
+import logging
+from collections.abc import AsyncIterator, Iterator
+from typing import Any
+
+from ..adapters import extract_anthropic_native
+
+logger = logging.getLogger("lago_agent_sdk.wrappers.anthropic")
+
+_INSTRUMENTED_ATTR = "_lago_instrumented"
+_LAGO_KWARG = "extra_lago"
+
+
+def _pop_lago_kwarg(kwargs: dict[str, Any]) -> dict[str, Any]:
+    return kwargs.pop(_LAGO_KWARG, {}) or {}
+
+
+def _is_message_like(obj: Any) -> bool:
+    """Anthropic Message objects expose `.usage` and `.content`; streams don't.
+
+    Safe against properties that raise — falls through to False so the customer's
+    call is never broken by attribute-access surprises in their custom objects.
+    """
+    try:
+        if isinstance(obj, dict):
+            return "usage" in obj
+        # hasattr propagates non-AttributeError exceptions on Py3; guard explicitly.
+        return hasattr(obj, "usage")
+    except Exception:  # noqa: BLE001
+        return False
+
+
+def wrap_anthropic_client(
+    sdk: Any,
+    client: Any,
+    dimensions: dict[str, Any] | None = None,
+    subscription: str | None = None,
+) -> Any:
+    """In-place wrap of an `anthropic.Anthropic` or `anthropic.AsyncAnthropic` client. Idempotent."""
+    if getattr(client, _INSTRUMENTED_ATTR, False):
+        logger.info("lago: anthropic client already wrapped — skipping")
+        return client
+
+    base_dims = dict(dimensions or {})
+    base_sub = subscription
+
+    messages = getattr(client, "messages", None)
+    if messages is None:
+        logger.warning("lago: anthropic client has no .messages — skipping wrap")
+        return client
+
+    original_create = getattr(messages, "create", None)
+    original_stream = getattr(messages, "stream", None)
+    is_async = type(client).__name__.startswith("Async")
+
+    def _resolve_opts(lago_opts: dict[str, Any]) -> tuple[str | None, dict[str, Any]]:
+        sub = lago_opts.get("subscription") or base_sub
+        dims = {**base_dims, **(lago_opts.get("dimensions") or {})}
+        return sub, dims
+
+    def _emit_from(payload: Any, model_id: str, sub: str | None, dims: dict[str, Any]) -> None:
+        try:
+            usage = extract_anthropic_native(payload, model_id=model_id)
+            sdk.emit(usage, subscription=sub, dimensions=dims)
+        except Exception as exc:  # noqa: BLE001
+            logger.warning("lago: anthropic emit failed: %s", exc)
+
+    # ------------------------------------------------------------------
+    # Sync messages.create — auto-detects streaming via response shape
+    # ------------------------------------------------------------------
+    def _create(*args: Any, **kwargs: Any) -> Any:
+        assert original_create is not None
+        lago_opts = _pop_lago_kwarg(kwargs)
+        model_id = kwargs.get("model", "")
+        sub, dims = _resolve_opts(lago_opts)
+        response = original_create(*args, **kwargs)
+
+        if _is_message_like(response):
+            _emit_from(response, model_id, sub, dims)
+            return response
+
+        # Streaming — wrap the iterator to capture the final usage on close.
+        def _wrap_stream(src: Iterator[Any]) -> Iterator[Any]:
+            last_usage: dict[str, Any] | None = None
+            try:
+                for event in src:
+                    payload = event.model_dump() if hasattr(event, "model_dump") else event
+                    if isinstance(payload, dict):
+                        usage = payload.get("usage")
+                        if isinstance(usage, dict):
+                            last_usage = {"usage": usage}
+                    yield event
+            finally:
+                if last_usage is not None:
+                    _emit_from(last_usage, model_id, sub, dims)
+
+        return _wrap_stream(response)
+
+    # ------------------------------------------------------------------
+    # Async messages.create — same as sync, awaited
+    # ------------------------------------------------------------------
+    async def _create_async(*args: Any, **kwargs: Any) -> Any:
+        assert original_create is not None
+        lago_opts = _pop_lago_kwarg(kwargs)
+        model_id = kwargs.get("model", "")
+        sub, dims = _resolve_opts(lago_opts)
+        response = await original_create(*args, **kwargs)
+
+        if _is_message_like(response):
+            _emit_from(response, model_id, sub, dims)
+            return response
+
+        async def _wrap_async_stream(src: AsyncIterator[Any]) -> AsyncIterator[Any]:
+            last_usage: dict[str, Any] | None = None
+            try:
+                async for event in src:
+                    payload = event.model_dump() if hasattr(event, "model_dump") else event
+                    if isinstance(payload, dict):
+                        usage = payload.get("usage")
+                        if isinstance(usage, dict):
+                            last_usage = {"usage": usage}
+                    yield event
+            finally:
+                if last_usage is not None:
+                    _emit_from(last_usage, model_id, sub, dims)
+
+        return _wrap_async_stream(response)
+
+    # ------------------------------------------------------------------
+    # messages.stream context manager (sync + async)
+    #
+    # Anthropic returns a MessageStreamManager (sync) / AsyncMessageStreamManager
+    # (async). Both have .__enter__/.__exit__ and the inner stream object
+    # exposes .get_final_message() after the with-block closes.
+    # ------------------------------------------------------------------
+    def _wrap_stream_manager(*args: Any, **kwargs: Any) -> Any:
+        assert original_stream is not None
+        lago_opts = _pop_lago_kwarg(kwargs)
+        model_id = kwargs.get("model", "")
+        sub, dims = _resolve_opts(lago_opts)
+        inner = original_stream(*args, **kwargs)
+        return _LagoStreamManager(inner, sdk, model_id, sub, dims, is_async=is_async)
+
+    if original_create is not None:
+        messages.create = _create_async if is_async else _create
+    if original_stream is not None:
+        messages.stream = _wrap_stream_manager
+
+    setattr(client, _INSTRUMENTED_ATTR, True)
+    return client
+
+
+class _LagoStreamManager:
+    """Proxies Anthropic's MessageStreamManager and emits on close.
+
+    Works for both sync (`with`) and async (`async with`) variants by detecting
+    which __exit__ kind is being called.
+    """
+
+    def __init__(
+        self,
+        inner: Any,
+        sdk: Any,
+        model_id: str,
+        sub: str | None,
+        dims: dict[str, Any],
+        *,
+        is_async: bool,
+    ) -> None:
+        self._inner = inner
+        self._sdk = sdk
+        self._model_id = model_id
+        self._sub = sub
+        self._dims = dims
+        self._stream: Any = None
+        self._is_async = is_async
+
+    # ----- sync -----
+    def __enter__(self) -> Any:
+        self._stream = self._inner.__enter__()
+        return self._stream
+
+    def __exit__(self, exc_type: Any, exc: Any, tb: Any) -> Any:
+        try:
+            result = self._inner.__exit__(exc_type, exc, tb)
+        finally:
+            self._emit_final()
+        return result
+
+    # ----- async -----
+    async def __aenter__(self) -> Any:
+        self._stream = await self._inner.__aenter__()
+        return self._stream
+
+    async def __aexit__(self, exc_type: Any, exc: Any, tb: Any) -> Any:
+        try:
+            result = await self._inner.__aexit__(exc_type, exc, tb)
+        finally:
+            self._emit_final()
+        return result
+
+    def _emit_final(self) -> None:
+        try:
+            final = (
+                self._stream.get_final_message()
+                if self._stream and hasattr(self._stream, "get_final_message")
+                else None
+            )
+            if final is not None:
+                from ..adapters import extract_anthropic_native
+
+                usage = extract_anthropic_native(final, model_id=self._model_id)
+                self._sdk.emit(usage, subscription=self._sub, dimensions=self._dims)
+        except Exception as exc:  # noqa: BLE001
+            logger.warning("lago: anthropic stream-manager emit failed: %s", exc)
diff --git a/tests/integration/test_live_anthropic.py b/tests/integration/test_live_anthropic.py
new file mode 100644
index 0000000..1b60e67
--- /dev/null
+++ b/tests/integration/test_live_anthropic.py
@@ -0,0 +1,114 @@
+"""End-to-end Anthropic integration test — live API + mocked Lago.
+
+Skipped unless ANTHROPIC_API_KEY is set.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+
+import pytest
+
+from lago_agent_sdk import LagoSDK
+
+pytestmark = pytest.mark.skipif(
+    not os.environ.get("ANTHROPIC_API_KEY"),
+    reason="ANTHROPIC_API_KEY not set",
+)
+
+
+class _MockLago(BaseHTTPRequestHandler):
+    def do_POST(self):  # noqa: N802
+        n = int(self.headers.get("Content-Length", 0))
+        body = self.rfile.read(n)
+        self.server.received.append(json.loads(body))  # type: ignore[attr-defined]
+        self.send_response(200)
+        self.send_header("Content-Type", "application/json")
+        self.end_headers()
+        self.wfile.write(b'{"ok": true}')
+
+    def log_message(self, *_args, **_kwargs):
+        return
+
+
+def _spawn_lago():
+    s = HTTPServer(("127.0.0.1", 0), _MockLago)
+    s.received = []  # type: ignore[attr-defined]
+    threading.Thread(target=s.serve_forever, daemon=True).start()
+    return s, f"http://127.0.0.1:{s.server_port}"
+
+
+def test_live_anthropic_messages_create_emits_to_lago() -> None:
+    from anthropic import Anthropic
+
+    server, url = _spawn_lago()
+    try:
+        sdk = LagoSDK(api_key="x", api_url=url, default_subscription_id="sub_int")
+        client = sdk.wrap(Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]))
+        client.messages.create(
+            model="claude-haiku-4-5-20251001",
+            max_tokens=20,
+            messages=[{"role": "user", "content": "Say hi"}],
+        )
+        assert sdk.flush(timeout=10.0)
+        sdk.shutdown(timeout=2.0)
+        events = [e for p in server.received for e in p["events"]]  # type: ignore[attr-defined]
+        codes = {e["code"] for e in events}
+        assert "llm_input_tokens" in codes
+        assert "llm_output_tokens" in codes
+        for e in events:
+            assert e["properties"]["api"] == "native"
+            assert e["properties"]["provider"] == "anthropic"
+    finally:
+        server.shutdown()
+
+
+def test_live_anthropic_streaming_emits_from_final_delta() -> None:
+    from anthropic import Anthropic
+
+    server, url = _spawn_lago()
+    try:
+        sdk = LagoSDK(api_key="x", api_url=url, default_subscription_id="sub_int")
+        client = sdk.wrap(Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]))
+        for _ in client.messages.create(
+            model="claude-haiku-4-5-20251001",
+            max_tokens=20,
+            messages=[{"role": "user", "content": "Say hi"}],
+            stream=True,
+        ):
+            pass
+        assert sdk.flush(timeout=10.0)
+        sdk.shutdown(timeout=2.0)
+        events = [e for p in server.received for e in p["events"]]  # type: ignore[attr-defined]
+        codes = {e["code"] for e in events}
+        assert "llm_input_tokens" in codes
+        assert "llm_output_tokens" in codes
+    finally:
+        server.shutdown()
+
+
+def test_live_anthropic_messages_stream_context_manager() -> None:
+    from anthropic import Anthropic
+
+    server, url = _spawn_lago()
+    try:
+        sdk = LagoSDK(api_key="x", api_url=url, default_subscription_id="sub_int")
+        client = sdk.wrap(Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]))
+        with client.messages.stream(
+            model="claude-haiku-4-5-20251001",
+            max_tokens=20,
+            messages=[{"role": "user", "content": "Say hi"}],
+        ) as stream:
+            for _ in stream.text_stream:
+                pass
+        assert sdk.flush(timeout=10.0)
+        sdk.shutdown(timeout=2.0)
+        events = [e for p in server.received for e in p["events"]]  # type: ignore[attr-defined]
+        codes = {e["code"] for e in events}
+        assert "llm_input_tokens" in codes
+        assert "llm_output_tokens" in codes
+    finally:
+        server.shutdown()
diff --git a/tests/unit/adapters/fixtures/anthropic_native/01_plain_haiku.json b/tests/unit/adapters/fixtures/anthropic_native/01_plain_haiku.json
new file mode 100644
index 0000000..ebe80c3
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/01_plain_haiku.json
@@ -0,0 +1,33 @@
+{
+  "_model_id": "claude-haiku-4-5-20251001",
+  "_response": {
+    "id": "msg_014oRrBt8p4HqV5k5eS1RyKN",
+    "container": null,
+    "content": [
+      {
+        "citations": null,
+        "text": "Dolphins are highly intelligent marine mammals known for their playful behavior, complex social structures, and remarkable ability to communicate with each other through clicks and whistles.",
+        "type": "text"
+      }
+    ],
+    "model": "claude-haiku-4-5-20251001",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "end_turn",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 0,
+        "ephemeral_5m_input_tokens": 0
+      },
+      "cache_creation_input_tokens": 0,
+      "cache_read_input_tokens": 0,
+      "inference_geo": "not_available",
+      "input_tokens": 13,
+      "output_tokens": 35,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/02_plain_sonnet.json b/tests/unit/adapters/fixtures/anthropic_native/02_plain_sonnet.json
new file mode 100644
index 0000000..36071ff
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/02_plain_sonnet.json
@@ -0,0 +1,33 @@
+{
+  "_model_id": "claude-sonnet-4-6",
+  "_response": {
+    "id": "msg_01Y3fakcdpcj6tk6FJrxV5GJ",
+    "container": null,
+    "content": [
+      {
+        "citations": null,
+        "text": "Dolphins are highly intelligent marine mammals known for their playful behavior, complex social bonds, and remarkable ability to communicate using a variety of clicks, whistles, and other sounds.",
+        "type": "text"
+      }
+    ],
+    "model": "claude-sonnet-4-6",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "end_turn",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 0,
+        "ephemeral_5m_input_tokens": 0
+      },
+      "cache_creation_input_tokens": 0,
+      "cache_read_input_tokens": 0,
+      "inference_geo": "global",
+      "input_tokens": 13,
+      "output_tokens": 39,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/03_tool_use.json b/tests/unit/adapters/fixtures/anthropic_native/03_tool_use.json
new file mode 100644
index 0000000..5dc4e83
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/03_tool_use.json
@@ -0,0 +1,39 @@
+{
+  "_model_id": "claude-sonnet-4-6",
+  "_response": {
+    "id": "msg_01FBZLSB8UduV9akqUkEtyEW",
+    "container": null,
+    "content": [
+      {
+        "id": "toolu_01AMkoyrfvRgYBCA21zpGXNi",
+        "caller": {
+          "type": "direct"
+        },
+        "input": {
+          "city": "Tokyo"
+        },
+        "name": "get_weather",
+        "type": "tool_use"
+      }
+    ],
+    "model": "claude-sonnet-4-6",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "tool_use",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 0,
+        "ephemeral_5m_input_tokens": 0
+      },
+      "cache_creation_input_tokens": 0,
+      "cache_read_input_tokens": 0,
+      "inference_geo": "global",
+      "input_tokens": 658,
+      "output_tokens": 38,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/04_cache_create_5m.json b/tests/unit/adapters/fixtures/anthropic_native/04_cache_create_5m.json
new file mode 100644
index 0000000..2fdaf1f
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/04_cache_create_5m.json
@@ -0,0 +1,33 @@
+{
+  "_model_id": "claude-sonnet-4-6",
+  "_response": {
+    "id": "msg_01VtgdQSaox4WMdGvHipchpn",
+    "container": null,
+    "content": [
+      {
+        "citations": null,
+        "text": "**4**\n\nSteps:\n1. Start with 2\n2. Add 2\n3. Result = **4**",
+        "type": "text"
+      }
+    ],
+    "model": "claude-sonnet-4-6",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "end_turn",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 0,
+        "ephemeral_5m_input_tokens": 2803
+      },
+      "cache_creation_input_tokens": 2803,
+      "cache_read_input_tokens": 0,
+      "inference_geo": "global",
+      "input_tokens": 13,
+      "output_tokens": 30,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/05_cache_read.json b/tests/unit/adapters/fixtures/anthropic_native/05_cache_read.json
new file mode 100644
index 0000000..c7fc4bb
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/05_cache_read.json
@@ -0,0 +1,33 @@
+{
+  "_model_id": "claude-sonnet-4-6",
+  "_response": {
+    "id": "msg_011bpj3E8EKkiNzynaPfBuJu",
+    "container": null,
+    "content": [
+      {
+        "citations": null,
+        "text": "**3 + 3 = 6**\n\n**Step 1:** Start with 3.\n**Step 2:** Add ",
+        "type": "text"
+      }
+    ],
+    "model": "claude-sonnet-4-6",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "max_tokens",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 0,
+        "ephemeral_5m_input_tokens": 0
+      },
+      "cache_creation_input_tokens": 0,
+      "cache_read_input_tokens": 2803,
+      "inference_geo": "global",
+      "input_tokens": 13,
+      "output_tokens": 30,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/06_cache_create_1h.json b/tests/unit/adapters/fixtures/anthropic_native/06_cache_create_1h.json
new file mode 100644
index 0000000..8624bc4
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/06_cache_create_1h.json
@@ -0,0 +1,33 @@
+{
+  "_model_id": "claude-sonnet-4-6",
+  "_response": {
+    "id": "msg_01CnMDjYpfBiy7JWKyMeNWsL",
+    "container": null,
+    "content": [
+      {
+        "citations": null,
+        "text": "Hi! How can I help you today?",
+        "type": "text"
+      }
+    ],
+    "model": "claude-sonnet-4-6",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "end_turn",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 2808,
+        "ephemeral_5m_input_tokens": 0
+      },
+      "cache_creation_input_tokens": 2808,
+      "cache_read_input_tokens": 0,
+      "inference_geo": "global",
+      "input_tokens": 7,
+      "output_tokens": 12,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/07_extended_thinking.json b/tests/unit/adapters/fixtures/anthropic_native/07_extended_thinking.json
new file mode 100644
index 0000000..4d0002d
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/07_extended_thinking.json
@@ -0,0 +1,38 @@
+{
+  "_model_id": "claude-sonnet-4-6",
+  "_response": {
+    "id": "msg_01EAk8qJYaKDY7YNx6hiKBta",
+    "container": null,
+    "content": [
+      {
+        "signature": "ErQCCmUIDRgCKkCFY8OE3VsRVnV6nXU/77sHcbai8ab7vVMPJKrFLAG73brAKyvMuOUHY3F3hARXd9ZCb++Z1sJ6emEjEdif2OwRMhFjbGF1ZGUtc29ubmV0LTQtNjgAQgh0aGlua2luZxIM6cZezoae3YMBKeUHGgw/iy0PoRrY0tY3z48iML7CqI0ZluxPJPXTAI3QxkdVG3dzXfxNpDhRWvOHvrURM5KpKm8gasgo5LLIJfQa0ip9EvggIrnDJKCXnOk5BFOsoNUe+2QdTzF7tGepNuhmB9R10uJzdEft/L/pw847GzejnrRYrahkVoNAv8hx/tiQABnoEbPqLixGimf2FhSMEUzzaHHoYiNlIdaR9cCZOXQ3hgyKrfkjg004wt6SaCLbZxm5SLZ8Yi5gsgVC0kAYAQ==",
+        "thinking": "We need to prove that 1\u00b3 + 2\u00b3 + 3\u00b3 + ... + n\u00b3 = (1 + 2 + 3 + ... + n)\u00b2\n\nI'll use mathematical induction.",
+        "type": "thinking"
+      },
+      {
+        "citations": null,
+        "text": "# Proof: Sum of First n Cubes\n\n## Statement to Prove\n\n$$\\sum_{k=1}^{n} k^3 = \\left(\\sum_{k=1}^{n} k\\right)^2$$\n\nUsing the known closed form for the linear sum, this is equivalent to:\n\n$$1^3 + 2^3 + 3^3 + \\cdots + n^3 = \\left(\\frac{n(n+1)}{2}\\right)^2$$\n\n## Proof by Mathematical Induction\n\n### Base Case (n = 1)\n\n**Left side:** $1^3 = 1$\n\n**Right side:** $\\left(\\dfrac{1 \\cdot 2}{2}\\right)^2 = (1)^2 = 1$ \u2713\n\n### Inductive Step\n\n**Inductive Hypothesis:** Assume the statement holds for some $n = m \\geq 1$:\n\n$$1^3 + 2^3 + \\cdots + m^3 = \\left(\\frac{m(m+1)}{2}\\right)^2$$\n\n**Goal:** Prove the statement holds for $n = m + 1$:\n\n$$1^3 + 2^3 + \\cdots + m^3 + (m+1)^3 = \\left(\\frac{(m+1)(m+2)}{2}\\right)^2$$\n\n**Derivation:**\n\nStarting with the left side of the goal:\n\n$$\\underbrace{1^3 + 2^3 + \\cdots + m^3}_{\\text{apply hypothesis}} + (m+1)^3$$\n\n$$= \\left(\\frac{m(m+1)}{2}\\right)^2 + (m+1)^3$$\n\n$$= \\frac{m^2(m+1)^2}{4} + (m+1)^3$$\n\nFactor out $(m+1)^2$:\n\n$$= (m+1)^2\\left(\\frac{m^2}{4} + (m+1)\\right)$$\n\nCombine terms inside the parentheses over a common denominator of 4:\n\n$$= (m+1)^2\\left(\\frac{m^2 + 4(m+1)}{4}\\right)$$\n\n$$= (m+1)^2\\left(\\frac{m^2 + 4m + 4}{4}\\right)$$\n\nFactor the numerator as a perfect square:\n\n$$= (m+1)^2\\left(\\frac{(m+2)^2}{4}\\right)$$\n\nRearrange:\n\n$$= \\frac{(m+1)^2(m+2)^2}{4}$$\n\n$$= \\left(\\frac{(m+1)(m+2)}{2}\\right)^2$$\n\nThis is exactly the right side of the goal. $\\blacksquare$\n\n## Conclusion\n\nBy the principle of mathematical induction, for all positive integers $n$:\n\n$$\\boxed{1^3 + 2^3 + 3^3 + \\cdots + n^3 = \\left(\\frac{n(n+1)}{2}\\right)^2 = \\left(1 + 2 + 3 + \\cdots + n\\right)^2}$$",
+        "type": "text"
+      }
+    ],
+    "model": "claude-sonnet-4-6",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "end_turn",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 0,
+        "ephemeral_5m_input_tokens": 0
+      },
+      "cache_creation_input_tokens": 0,
+      "cache_read_input_tokens": 0,
+      "inference_geo": "global",
+      "input_tokens": 66,
+      "output_tokens": 862,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/08_stream.json b/tests/unit/adapters/fixtures/anthropic_native/08_stream.json
new file mode 100644
index 0000000..6b55d43
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/08_stream.json
@@ -0,0 +1,142 @@
+{
+  "_model_id": "claude-haiku-4-5-20251001",
+  "_response": {
+    "events": [
+      {
+        "message": {
+          "id": "msg_01A9ASsVixqCzpb4qwbcCkd2",
+          "container": null,
+          "content": [],
+          "model": "claude-haiku-4-5-20251001",
+          "role": "assistant",
+          "stop_details": null,
+          "stop_reason": null,
+          "stop_sequence": null,
+          "type": "message",
+          "usage": {
+            "cache_creation": {
+              "ephemeral_1h_input_tokens": 0,
+              "ephemeral_5m_input_tokens": 0
+            },
+            "cache_creation_input_tokens": 0,
+            "cache_read_input_tokens": 0,
+            "inference_geo": "not_available",
+            "input_tokens": 13,
+            "output_tokens": 8,
+            "server_tool_use": null,
+            "service_tier": "standard"
+          }
+        },
+        "type": "message_start"
+      },
+      {
+        "content_block": {
+          "citations": null,
+          "text": "",
+          "type": "text"
+        },
+        "index": 0,
+        "type": "content_block_start"
+      },
+      {
+        "delta": {
+          "text": "Dolphins are highly intelligent marine mammals known",
+          "type": "text_delta"
+        },
+        "index": 0,
+        "type": "content_block_delta"
+      },
+      {
+        "type": "text",
+        "text": "Dolphins are highly intelligent marine mammals known",
+        "snapshot": "Dolphins are highly intelligent marine mammals known"
+      },
+      {
+        "delta": {
+          "text": " for their playful behavior, complex social structures, and remarkable ability to communicate with each other through clicks",
+          "type": "text_delta"
+        },
+        "index": 0,
+        "type": "content_block_delta"
+      },
+      {
+        "type": "text",
+        "text": " for their playful behavior, complex social structures, and remarkable ability to communicate with each other through clicks",
+        "snapshot": "Dolphins are highly intelligent marine mammals known for their playful behavior, complex social structures, and remarkable ability to communicate with each other through clicks"
+      },
+      {
+        "delta": {
+          "text": " and whistles.",
+          "type": "text_delta"
+        },
+        "index": 0,
+        "type": "content_block_delta"
+      },
+      {
+        "type": "text",
+        "text": " and whistles.",
+        "snapshot": "Dolphins are highly intelligent marine mammals known for their playful behavior, complex social structures, and remarkable ability to communicate with each other through clicks and whistles."
+      },
+      {
+        "index": 0,
+        "type": "content_block_stop",
+        "content_block": {
+          "citations": null,
+          "text": "Dolphins are highly intelligent marine mammals known for their playful behavior, complex social structures, and remarkable ability to communicate with each other through clicks and whistles.",
+          "type": "text",
+          "parsed_output": null
+        }
+      },
+      {
+        "delta": {
+          "container": null,
+          "stop_details": null,
+          "stop_reason": "end_turn",
+          "stop_sequence": null
+        },
+        "type": "message_delta",
+        "usage": {
+          "cache_creation_input_tokens": 0,
+          "cache_read_input_tokens": 0,
+          "input_tokens": 13,
+          "output_tokens": 35,
+          "server_tool_use": null
+        }
+      },
+      {
+        "type": "message_stop",
+        "message": {
+          "id": "msg_01A9ASsVixqCzpb4qwbcCkd2",
+          "container": null,
+          "content": [
+            {
+              "citations": null,
+              "text": "Dolphins are highly intelligent marine mammals known for their playful behavior, complex social structures, and remarkable ability to communicate with each other through clicks and whistles.",
+              "type": "text",
+              "parsed_output": null
+            }
+          ],
+          "model": "claude-haiku-4-5-20251001",
+          "role": "assistant",
+          "stop_details": null,
+          "stop_reason": "end_turn",
+          "stop_sequence": null,
+          "type": "message",
+          "usage": {
+            "cache_creation": {
+              "ephemeral_1h_input_tokens": 0,
+              "ephemeral_5m_input_tokens": 0
+            },
+            "cache_creation_input_tokens": 0,
+            "cache_read_input_tokens": 0,
+            "inference_geo": "not_available",
+            "input_tokens": 13,
+            "output_tokens": 35,
+            "server_tool_use": null,
+            "service_tier": "standard"
+          }
+        }
+      }
+    ]
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/anthropic_native/09_multi_turn.json b/tests/unit/adapters/fixtures/anthropic_native/09_multi_turn.json
new file mode 100644
index 0000000..eb3ff9c
--- /dev/null
+++ b/tests/unit/adapters/fixtures/anthropic_native/09_multi_turn.json
@@ -0,0 +1,33 @@
+{
+  "_model_id": "claude-haiku-4-5-20251001",
+  "_response": {
+    "id": "msg_01Tg1sNzgCXenQnUBLwQ8Ycr",
+    "container": null,
+    "content": [
+      {
+        "citations": null,
+        "text": "4 times 3 equals 12.",
+        "type": "text"
+      }
+    ],
+    "model": "claude-haiku-4-5-20251001",
+    "role": "assistant",
+    "stop_details": null,
+    "stop_reason": "end_turn",
+    "stop_sequence": null,
+    "type": "message",
+    "usage": {
+      "cache_creation": {
+        "ephemeral_1h_input_tokens": 0,
+        "ephemeral_5m_input_tokens": 0
+      },
+      "cache_creation_input_tokens": 0,
+      "cache_read_input_tokens": 0,
+      "inference_geo": "not_available",
+      "input_tokens": 34,
+      "output_tokens": 14,
+      "server_tool_use": null,
+      "service_tier": "standard"
+    }
+  }
+}
\ No newline at end of file
diff --git a/tests/unit/adapters/fixtures/capture_anthropic.py b/tests/unit/adapters/fixtures/capture_anthropic.py
new file mode 100644
index 0000000..73893a2
--- /dev/null
+++ b/tests/unit/adapters/fixtures/capture_anthropic.py
@@ -0,0 +1,179 @@
+"""Capture real Anthropic native API responses for adapter design.
+
+Saves raw responses to tests/unit/adapters/fixtures/anthropic_native/<scenario>.json
+so we can verify mappings against reality before writing the adapter.
+
+Reads ANTHROPIC_API_KEY from env.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import pathlib
+import sys
+
+from anthropic import Anthropic
+
+OUT = pathlib.Path(__file__).parent / "anthropic_native"
+OUT.mkdir(parents=True, exist_ok=True)
+
+
+def to_dict(response) -> dict:
+    """Anthropic SDK returns pydantic models — convert to plain dict for JSON."""
+    if hasattr(response, "model_dump"):
+        return response.model_dump()
+    if hasattr(response, "dict"):
+        return response.dict()
+    return json.loads(response.json()) if hasattr(response, "json") else dict(response)
+
+
+def save(name: str, model: str, payload: dict) -> None:
+    path = OUT / f"{name}.json"
+    path.write_text(json.dumps({"_model_id": model, "_response": payload}, indent=2, default=str))
+    print(f"  ✓ saved {path.name}")
+
+
+def main() -> int:
+    key = os.environ.get("ANTHROPIC_API_KEY")
+    if not key:
+        print("error: set ANTHROPIC_API_KEY", file=sys.stderr)
+        return 2
+
+    client = Anthropic(api_key=key)
+    PROMPT = "Write one sentence about dolphins."
+
+    # Rename badge: the script header reads "Sonnet 4.5" but the API only exposes 4-6+ now.
+    # ----- 1. Plain call (small model) -----
+    print("\n[1] plain — claude-haiku-4-5-20251001")
+    r = client.messages.create(
+        model="claude-haiku-4-5-20251001",
+        max_tokens=80,
+        messages=[{"role": "user", "content": PROMPT}],
+    )
+    save("01_plain_haiku", "claude-haiku-4-5-20251001", to_dict(r))
+
+    # ----- 2. Plain call (Sonnet, larger) -----
+    print("\n[2] plain — claude-sonnet-4-6")
+    r = client.messages.create(
+        model="claude-sonnet-4-6",
+        max_tokens=80,
+        messages=[{"role": "user", "content": PROMPT}],
+    )
+    save("02_plain_sonnet", "claude-sonnet-4-6", to_dict(r))
+
+    # ----- 3. Tool use -----
+    print("\n[3] tool use — claude-sonnet-4-6 with weather tool")
+    tools = [
+        {
+            "name": "get_weather",
+            "description": "Get the current weather for a city.",
+            "input_schema": {
+                "type": "object",
+                "properties": {"city": {"type": "string"}},
+                "required": ["city"],
+            },
+        }
+    ]
+    r = client.messages.create(
+        model="claude-sonnet-4-6",
+        max_tokens=200,
+        tools=tools,
+        tool_choice={"type": "any"},
+        messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
+    )
+    save("03_tool_use", "claude-sonnet-4-6", to_dict(r))
+
+    # ----- 4. Cache create (5m default TTL) — long system prompt -----
+    print("\n[4] cache create — long system + cache_control 5m default")
+    LONG_TEXT = ("You are a helpful assistant. Answer concisely. " * 200) + (
+        "Always cite step by step. " * 100
+    )
+    cached_body = {
+        "model": "claude-sonnet-4-6",
+        "max_tokens": 30,
+        "system": [{"type": "text", "text": LONG_TEXT, "cache_control": {"type": "ephemeral"}}],
+        "messages": [{"role": "user", "content": "What's 2+2?"}],
+    }
+    r = client.messages.create(**cached_body)
+    save("04_cache_create_5m", "claude-sonnet-4-6", to_dict(r))
+
+    # ----- 5. Cache read (same long system, different user question) -----
+    print("\n[5] cache read — same cached_control content, second call")
+    cached_body["messages"] = [{"role": "user", "content": "What's 3+3?"}]
+    r = client.messages.create(**cached_body)
+    save("05_cache_read", "claude-sonnet-4-6", to_dict(r))
+
+    # ----- 6. Cache 1h TTL -----
+    print("\n[6] cache 1h — explicit ttl")
+    cached_1h = {
+        "model": "claude-sonnet-4-6",
+        "max_tokens": 30,
+        "system": [
+            {
+                "type": "text",
+                "text": LONG_TEXT + " (1h variant)",
+                "cache_control": {"type": "ephemeral", "ttl": "1h"},
+            }
+        ],
+        "messages": [{"role": "user", "content": "Hi"}],
+    }
+    try:
+        r = client.messages.create(**cached_1h)
+        save("06_cache_create_1h", "claude-sonnet-4-6", to_dict(r))
+    except Exception as exc:  # noqa: BLE001
+        print(f"  1h TTL not available on this account/region: {str(exc)[:160]}")
+
+    # ----- 7. Extended thinking (reasoning) -----
+    print("\n[7] extended thinking — claude-sonnet-4-6")
+    try:
+        r = client.messages.create(
+            model="claude-sonnet-4-6",
+            max_tokens=2048,
+            thinking={"type": "enabled", "budget_tokens": 1024},
+            messages=[
+                {
+                    "role": "user",
+                    "content": (
+                        "Prove that the sum of the first n cubes equals the square of the sum of "
+                        "the first n positive integers. Show each algebraic step."
+                    ),
+                }
+            ],
+        )
+        save("07_extended_thinking", "claude-sonnet-4-6", to_dict(r))
+    except Exception as exc:  # noqa: BLE001
+        print(f"  extended thinking error: {str(exc)[:160]}")
+
+    # ----- 8. Streaming -----
+    print("\n[8] streaming — claude-haiku-4-5-20251001")
+    events: list[dict] = []
+    with client.messages.stream(
+        model="claude-haiku-4-5-20251001",
+        max_tokens=60,
+        messages=[{"role": "user", "content": PROMPT}],
+    ) as stream:
+        for event in stream:
+            events.append(to_dict(event))
+    save("08_stream", "claude-haiku-4-5-20251001", {"events": events})
+
+    # ----- 9. Multi-turn -----
+    print("\n[9] multi-turn — claude-haiku-4-5-20251001")
+    convo = [
+        {"role": "user", "content": "What is 2+2?"},
+        {"role": "assistant", "content": "2+2 equals 4."},
+        {"role": "user", "content": "And times 3?"},
+    ]
+    r = client.messages.create(
+        model="claude-haiku-4-5-20251001",
+        max_tokens=40,
+        messages=convo,
+    )
+    save("09_multi_turn", "claude-haiku-4-5-20251001", to_dict(r))
+
+    print("\nDone. Inspect tests/unit/adapters/fixtures/anthropic_native/*.json")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tests/unit/adapters/test_anthropic_native.py b/tests/unit/adapters/test_anthropic_native.py
new file mode 100644
index 0000000..13bff69
--- /dev/null
+++ b/tests/unit/adapters/test_anthropic_native.py
@@ -0,0 +1,152 @@
+"""Anthropic native adapter — verified against real fixtures."""
+
+from __future__ import annotations
+
+import json
+import pathlib
+
+from lago_agent_sdk.adapters import extract_anthropic_native
+
+FIX = pathlib.Path(__file__).parent / "fixtures" / "anthropic_native"
+
+
+def _load(name: str) -> tuple[str, dict]:
+    data = json.loads((FIX / name).read_text())
+    return data["_model_id"], data["_response"]
+
+
+# --------------------------------------------------------------------------
+# Real fixtures
+# --------------------------------------------------------------------------
+def test_plain_haiku() -> None:
+    model_id, resp = _load("01_plain_haiku.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.input == 13
+    assert u.output == 35
+    assert u.cache_read == 0
+    assert u.cache_write == 0
+    assert u.tool_calls == 0
+    assert u.api == "native"
+    assert u.provider == "anthropic"
+    assert u.model == "claude-haiku-4-5-20251001"
+
+
+def test_plain_sonnet() -> None:
+    model_id, resp = _load("02_plain_sonnet.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.input == 13
+    assert u.output == 39
+
+
+def test_tool_use_counts_tool_calls() -> None:
+    model_id, resp = _load("03_tool_use.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.input == 658
+    assert u.output == 38
+    assert u.tool_calls == 1
+
+
+def test_cache_create_5m() -> None:
+    model_id, resp = _load("04_cache_create_5m.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.cache_write == 2803
+    assert u.cache_write_5m == 2803
+    assert u.cache_write_1h == 0
+    assert u.cache_read == 0
+
+
+def test_cache_read_after_create() -> None:
+    model_id, resp = _load("05_cache_read.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.cache_read == 2803
+    assert u.cache_write == 0
+    assert u.cache_write_5m == 0
+
+
+def test_cache_create_1h() -> None:
+    model_id, resp = _load("06_cache_create_1h.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.cache_write == 2808
+    assert u.cache_write_1h == 2808
+    assert u.cache_write_5m == 0
+
+
+def test_extended_thinking_bundles_into_output_tokens() -> None:
+    """Anthropic's extended thinking does NOT expose reasoning_tokens — they're folded into output_tokens."""
+    model_id, resp = _load("07_extended_thinking.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.input == 66
+    assert u.output == 862  # all 862 includes thinking + final answer
+    assert u.reasoning == 0  # confirmed: Anthropic doesn't separate it
+    # content has both 'thinking' and 'text' blocks — neither counts as a tool call
+    assert u.tool_calls == 0
+
+
+def test_multi_turn() -> None:
+    model_id, resp = _load("09_multi_turn.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert u.input == 34
+    assert u.output == 14
+
+
+def test_unknown_top_usage_field_lands_in_extras() -> None:
+    """service_tier, inference_geo, server_tool_use are new fields → drift detection."""
+    model_id, resp = _load("01_plain_haiku.json")
+    u = extract_anthropic_native(resp, model_id=model_id)
+    assert "service_tier" in u.extras
+    assert "inference_geo" in u.extras
+    assert "server_tool_use" in u.extras
+
+
+# --------------------------------------------------------------------------
+# Synthetic
+# --------------------------------------------------------------------------
+def test_handles_pydantic_via_model_dump() -> None:
+    class FakePydantic:
+        def model_dump(self) -> dict:
+            return {
+                "model": "claude-sonnet-4-6",
+                "content": [{"type": "text", "text": "hi"}],
+                "usage": {
+                    "input_tokens": 5,
+                    "output_tokens": 7,
+                    "cache_creation_input_tokens": 0,
+                    "cache_read_input_tokens": 0,
+                    "cache_creation": {
+                        "ephemeral_5m_input_tokens": 0,
+                        "ephemeral_1h_input_tokens": 0,
+                    },
+                },
+            }
+
+    u = extract_anthropic_native(FakePydantic(), model_id="claude-sonnet-4-6")
+    assert u.input == 5
+    assert u.output == 7
+    assert u.api == "native"
+
+
+def test_multiple_tool_use_blocks_counted() -> None:
+    resp = {
+        "usage": {"input_tokens": 10, "output_tokens": 20},
+        "content": [
+            {"type": "text", "text": "..."},
+            {"type": "tool_use", "id": "t1"},
+            {"type": "tool_use", "id": "t2"},
+            {"type": "tool_use", "id": "t3"},
+        ],
+    }
+    u = extract_anthropic_native(resp, model_id="claude-sonnet-4-6")
+    assert u.tool_calls == 3
+
+
+def test_no_usage_returns_zeros() -> None:
+    u = extract_anthropic_native({}, model_id="claude-sonnet-4-6")
+    assert u.input == 0
+    assert u.output == 0
+    assert not u.nonzero_numeric()
+
+
+def test_survives_non_dict_usage() -> None:
+    assert extract_anthropic_native({"usage": True}, model_id="x").input == 0
+    assert extract_anthropic_native({"usage": "bogus"}, model_id="x").output == 0
+    assert extract_anthropic_native(None, model_id="x").input == 0
diff --git a/tests/unit/test_buffer_overflow.py b/tests/unit/test_buffer_overflow.py
index 19d2e0f..d1c9907 100644
--- a/tests/unit/test_buffer_overflow.py
+++ b/tests/unit/test_buffer_overflow.py
@@ -45,7 +45,11 @@ def test_repeated_overflow_keeps_window_sliding():
     def slow_sender(batch):
         paused.wait(timeout=30.0)
 
-    q = EventQueue(sender=slow_sender, flush_interval=10.0, max_batch_size=100, max_buffer_size=100)
+    # max_batch_size > max_buffer_size keeps the background worker from ever
+    # being woken by push (buffer can't exceed max_batch_size). Combined with
+    # a long flush_interval, the test is deterministic — the worker only runs
+    # once shutdown() releases `paused` in the finally block.
+    q = EventQueue(sender=slow_sender, flush_interval=60.0, max_batch_size=10_000, max_buffer_size=100)
     try:
         for i in range(250):  # 150 events overflow
             q.push({"i": i})
diff --git a/tests/unit/test_wrapper_anthropic.py b/tests/unit/test_wrapper_anthropic.py
new file mode 100644
index 0000000..08c7a70
--- /dev/null
+++ b/tests/unit/test_wrapper_anthropic.py
@@ -0,0 +1,223 @@
+"""Anthropic wrapper tests — fake client, no live API."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from lago_agent_sdk import LagoSDK
+
+
+class FakeMessage:
+    """Mimics Anthropic's Message pydantic object."""
+
+    def __init__(self, payload: dict[str, Any]) -> None:
+        self._payload = payload
+        # expose .usage and .content as attribute access for _is_message_like check
+        self.usage = payload.get("usage")
+        self.content = payload.get("content", [])
+
+    def model_dump(self) -> dict[str, Any]:
+        return self._payload
+
+
+class FakeStreamEvent:
+    """Mimics one of Anthropic's MessageStreamEvent objects (MessageDelta/Start/etc.)."""
+
+    def __init__(self, payload: dict[str, Any]) -> None:
+        self._payload = payload
+
+    def model_dump(self) -> dict[str, Any]:
+        return self._payload
+
+
+class FakeMessages:
+    def __init__(self) -> None:
+        self.create_calls = 0
+        self.stream_calls = 0
+
+    def create(self, **kwargs: Any) -> Any:
+        self.create_calls += 1
+        assert "extra_lago" not in kwargs
+        if kwargs.get("stream") is True:
+            events = [
+                FakeStreamEvent({"type": "message_start", "message": {"usage": {"input_tokens": 12}}}),
+                FakeStreamEvent(
+                    {
+                        "type": "message_delta",
+                        "delta": {"stop_reason": "end_turn"},
+                        "usage": {"input_tokens": 12, "output_tokens": 22},
+                    }
+                ),
+                FakeStreamEvent({"type": "message_stop"}),
+            ]
+            return iter(events)
+        return FakeMessage(
+            {
+                "model": kwargs.get("model", "claude-sonnet-4-6"),
+                "content": [{"type": "text", "text": "hi"}],
+                "usage": {
+                    "input_tokens": 8,
+                    "output_tokens": 16,
+                    "cache_creation_input_tokens": 0,
+                    "cache_read_input_tokens": 0,
+                    "cache_creation": {
+                        "ephemeral_5m_input_tokens": 0,
+                        "ephemeral_1h_input_tokens": 0,
+                    },
+                },
+            }
+        )
+
+    def stream(self, **kwargs: Any) -> Any:
+        self.stream_calls += 1
+        assert "extra_lago" not in kwargs
+        outer = self
+
+        class _FakeStreamManager:
+            def __enter__(self_inner) -> Any:
+                outer._final = FakeMessage(
+                    {
+                        "model": kwargs.get("model", "claude-sonnet-4-6"),
+                        "content": [{"type": "text", "text": "hi"}],
+                        "usage": {
+                            "input_tokens": 5,
+                            "output_tokens": 11,
+                        },
+                    }
+                )
+                return _FakeStreamHandle(outer._final)
+
+            def __exit__(self_inner, exc_type, exc, tb) -> Any:  # noqa: D401
+                return False
+
+        return _FakeStreamManager()
+
+
+class _FakeStreamHandle:
+    def __init__(self, final: FakeMessage) -> None:
+        self._final = final
+        self.text_stream = iter(["hi"])
+
+    def get_final_message(self) -> FakeMessage:
+        return self._final
+
+
+class FakeAnthropic:
+    """Mimics `from anthropic import Anthropic; Anthropic(api_key=...)`."""
+
+    def __init__(self) -> None:
+        self.messages = FakeMessages()
+
+
+# Module path needs to contain 'anthropic' so detector.py routes to anthropic wrapper.
+FakeAnthropic.__module__ = "anthropic.fake"
+
+
+def _new_sdk(default_sub: str = "sub_test") -> tuple[LagoSDK, list[dict]]:
+    received: list[dict] = []
+
+    def sender(batch: list[dict]) -> None:
+        received.extend(batch)
+
+    sdk = LagoSDK(api_key="dummy", default_subscription_id=default_sub)
+    sdk._queue._sender = sender  # type: ignore[attr-defined]
+    return sdk, received
+
+
+def test_wrap_messages_create_emits_input_and_output() -> None:
+    sdk, received = _new_sdk()
+    fake = FakeAnthropic()
+    client = sdk.wrap(fake)
+    resp = client.messages.create(model="claude-sonnet-4-6", messages=[])
+    assert resp.usage["input_tokens"] == 8
+    assert sdk.flush(timeout=2.0)
+    sdk.shutdown(timeout=1.0)
+    by_code = {e["code"]: int(float(e["properties"]["value"])) for e in received}
+    assert by_code["llm_input_tokens"] == 8
+    assert by_code["llm_output_tokens"] == 16
+
+
+def test_wrap_strips_extra_lago_and_uses_per_call_sub() -> None:
+    sdk, received = _new_sdk("sub_default")
+    fake = FakeAnthropic()
+    client = sdk.wrap(fake)
+    client.messages.create(
+        model="claude-sonnet-4-6",
+        messages=[],
+        extra_lago={"subscription": "sub_per_call", "dimensions": {"feature": "X"}},
+    )
+    assert sdk.flush(timeout=2.0)
+    sdk.shutdown(timeout=1.0)
+    assert all(e["external_subscription_id"] == "sub_per_call" for e in received)
+    assert received[0]["properties"]["feature"] == "X"
+
+
+def test_wrap_double_wrap_is_idempotent() -> None:
+    sdk, received = _new_sdk()
+    fake = FakeAnthropic()
+    sdk.wrap(fake)
+    sdk.wrap(fake)
+    sdk.wrap(fake)
+    fake.messages.create(model="claude-sonnet-4-6", messages=[])
+    assert sdk.flush(timeout=2.0)
+    sdk.shutdown(timeout=1.0)
+    assert len(received) == 2  # input + output, not 6
+    assert fake.messages.create_calls == 1
+
+
+def test_wrap_create_with_stream_captures_usage_from_message_delta() -> None:
+    sdk, received = _new_sdk()
+    fake = FakeAnthropic()
+    client = sdk.wrap(fake)
+    events = list(client.messages.create(model="claude-sonnet-4-6", messages=[], stream=True))
+    assert len(events) == 3
+    assert sdk.flush(timeout=2.0)
+    sdk.shutdown(timeout=1.0)
+    by_code = {e["code"]: int(float(e["properties"]["value"])) for e in received}
+    assert by_code["llm_input_tokens"] == 12
+    assert by_code["llm_output_tokens"] == 22
+
+
+def test_wrap_messages_stream_context_manager_emits_on_close() -> None:
+    sdk, received = _new_sdk()
+    fake = FakeAnthropic()
+    client = sdk.wrap(fake)
+    with client.messages.stream(model="claude-sonnet-4-6", messages=[]) as stream:
+        list(stream.text_stream)
+    assert sdk.flush(timeout=2.0)
+    sdk.shutdown(timeout=1.0)
+    by_code = {e["code"]: int(float(e["properties"]["value"])) for e in received}
+    assert by_code["llm_input_tokens"] == 5
+    assert by_code["llm_output_tokens"] == 11
+
+
+def test_instrumentation_failure_does_not_break_call() -> None:
+    sdk, _ = _new_sdk()
+
+    class BadMessage:
+        @property
+        def usage(self):
+            raise RuntimeError("boom")
+
+        @property
+        def content(self):
+            return []
+
+        def model_dump(self):
+            raise RuntimeError("boom")
+
+    class BadMessages:
+        def create(self, **_kw):
+            return BadMessage()
+
+    class BadAnthropic:
+        def __init__(self):
+            self.messages = BadMessages()
+
+    BadAnthropic.__module__ = "anthropic.fake"
+
+    client = sdk.wrap(BadAnthropic())
+    # Adapter will crash inside, but wrap must still return resp.
+    resp = client.messages.create(model="x", messages=[])
+    assert resp is not None
+    sdk.shutdown(timeout=1.0)
diff --git a/uv.lock b/uv.lock
index f1fc5c8..a40fdc7 100644
--- a/uv.lock
+++ b/uv.lock
@@ -15,6 +15,25 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
+[[package]]
+name = "anthropic"
+version = "0.103.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "docstring-parser" },
+    { name = "httpx" },
+    { name = "jiter" },
+    { name = "pydantic" },
+    { name = "sniffio" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/fb/57/0b758b08cf4606c94d63a997d67a0063f7438efbaf81cfedd0d7c0c69d67/anthropic-0.103.1.tar.gz", hash = "sha256:21c12f4fc0fdd87a2e80d58479cd0af640062b3cfb82bbfa01c7977acd4defeb", size = 848877, upload-time = "2026-05-19T15:43:27.698Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/ad/ec/cf357cf571377a39552c1530390a9b79bbdb6ea463f48fbe4e3624141e3b/anthropic-0.103.1-py3-none-any.whl", hash = "sha256:b9a523fac34e64caf6ee55fdbda213950e6a744b906fce100d34909aad2cd8f4", size = 832551, upload-time = "2026-05-19T15:43:29.663Z" },
+]
+
 [[package]]
 name = "anyio"
 version = "4.13.0"
@@ -345,6 +364,24 @@ toml = [
     { name = "tomli", marker = "python_full_version <= '3.11'" },
 ]
 
+[[package]]
+name = "distro"
+version = "1.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/fc/f8/98eea607f65de6527f8a2e8885fc8015d3e6f5775df186e443e0964a11c3/distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed", size = 60722, upload-time = "2023-12-24T09:54:32.31Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277, upload-time = "2023-12-24T09:54:30.421Z" },
+]
+
+[[package]]
+name = "docstring-parser"
+version = "0.18.0"
+source = { registry = "https://pypi.org/simple" }
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+]
+
 [[package]]
 name = "jmespath"
 version = "1.1.0"
@@ -473,6 +613,9 @@ dependencies = [
 ]
 
 [package.optional-dependencies]
+anthropic = [
+    { name = "anthropic" },
+]
 bedrock = [
     { name = "boto3" },
 ]
@@ -491,8 +634,14 @@ mistral = [
     { name = "mistralai" },
 ]
 
+[package.dev-dependencies]
+dev = [
+    { name = "anthropic" },
+]
+
 [package.metadata]
 requires-dist = [
+    { name = "anthropic", marker = "extra == 'anthropic'", specifier = ">=0.30" },
     { name = "boto3", marker = "extra == 'bedrock'", specifier = ">=1.34" },
     { name = "boto3", marker = "extra == 'dev'", specifier = ">=1.34" },
     { name = "hypothesis", marker = "extra == 'dev'", specifier = ">=6" },
@@ -506,7 +655,10 @@ requires-dist = [
     { name = "ruff", marker = "extra == 'dev'", specifier = ">=0.6" },
     { name = "types-requests", marker = "extra == 'dev'", specifier = ">=2.31" },
 ]
-provides-extras = ["bedrock", "mistral", "dev"]
+provides-extras = ["bedrock", "mistral", "dev", "anthropic"]
+
+[package.metadata.requires-dev]
+dev = [{ name = "anthropic", specifier = ">=0.30" }]
 
 [[package]]
 name = "librt"
@@ -992,6 +1144,15 @@ wheels = [
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 ]
 
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a2/87/a6771e1546d97e7e041b6ae58d80074f81b7d5121207425c964ddf5cfdbd/sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc", size = 20372, upload-time = "2024-02-25T23:20:04.057Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e9/44/75a9c9421471a6c4805dbf2356f7c181a29c1879239abab1ea2cc8f38b40/sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", size = 10235, upload-time = "2024-02-25T23:20:01.196Z" },
+]
+
 [[package]]
 name = "sortedcontainers"
 version = "2.4.0"