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Perplexity WebUI Scraper

Python scraper to extract AI responses from Perplexity's web interface.

PyPI Python License


📚 Full Documentation & Advanced Guide: https://henrique-coder.github.io/perplexity-webui-scraper


What is this?

This library lets you interact with Perplexity AI programmatically using the same web endpoints as the browser — no official API key required. It supports conversations, file uploads, streaming, an MCP server for AI agents, and a drop-in OpenAI-compatible REST API.

  • Requirements: A Perplexity Pro or Max account and your browser session token.
  • Key Features: 15 models (GPT-5.4, Claude Opus, Gemini, Deep Research…), file attachments (images, PDFs, …), streaming, MCP Server for AI agents, OpenAI-compatible REST API, multi-turn conversation thread continuation.

Installation

Install the package depending on your use case:

As a Core Library

Install only the core python library without any extra dependencies.

uv add perplexity-webui-scraper

Full Installation (Everything)

Install all optional dependencies (cli, api, mcp) in one go. Recommended if you want to use all tools out-of-the-box.

uv add "perplexity-webui-scraper[all]"

CLI Tools

Install with terminal UX dependencies to use the interactive ask and token CLI commands.

uv add "perplexity-webui-scraper[cli]"

External Servers

Install dependencies required for the MCP Server or the OpenAI-compatible REST API.

# MCP Server for AI agents
uv add "perplexity-webui-scraper[mcp]"

# OpenAI-compatible API server
uv add "perplexity-webui-scraper[api]"

Quick Start

1. Get your session token

# Interactive CLI wizard — walks you through email auth
uv run perplexity-webui-scraper token

Or retrieve __Secure-next-auth.session-token manually from your browser cookies on perplexity.ai.

2. Basic usage

from perplexity_webui_scraper import Perplexity

client = Perplexity(session_token="YOUR_TOKEN")
conversation = client.create_conversation()

conversation.ask("What is quantum computing?")
print(conversation.answer)

# Follow-ups preserve context automatically
conversation.ask("Explain it simpler")
print(conversation.answer)

3. Streaming

for chunk in conversation.ask("Explain AI", stream=True):
    if chunk.last_chunk:
        print(chunk.last_chunk, end="", flush=True)

4. Choose a model

from perplexity_webui_scraper import ConversationConfig

conversation = client.create_conversation(ConversationConfig(model="perplexity/best"))
conversation.ask("Solve this step by step: ...")
print(conversation.answer)

5. List all available models

from perplexity_webui_scraper import MODELS

for model in MODELS.list_all():
    print(f"{model.id:40} {model.name}")

Available CLI

Command Extra Description
perplexity-webui-scraper token cli Interactive email auth wizard to generate a session token (supports TOTP 2FA)
perplexity-webui-scraper ask cli Ask Perplexity AI questions with real-time streaming output
perplexity-webui-scraper ask setup cli Configure saved token and default model for the ask command
perplexity-webui-scraper mcp mcp Start the MCP server
perplexity-webui-scraper api api Start the OpenAI-compatible REST API server

OpenAI-Compatible API

Run a local server that accepts OpenAI-formatted requests and forwards them to Perplexity. Works as a drop-in replacement for any OpenAI client — authentication is done per-request via Authorization: Bearer, exactly like the real API.

# Start the server (no token needed at startup)
perplexity-webui-scraper api

# Custom host and port
perplexity-webui-scraper api --host 0.0.0.0 --port 8080

# Development mode with auto-reload
perplexity-webui-scraper api --reload

Running via Container (Podman)

# Pull the published multi-arch API image
podman pull ghcr.io/henrique-coder/perplexity-webui-scraper:latest

# Run the server (exposing port 8000)
podman run --rm -p 8000:8000 ghcr.io/henrique-coder/perplexity-webui-scraper:latest

Optional MCP image for containerized stdio setups:

# Pull the published multi-arch MCP image
podman pull ghcr.io/henrique-coder/perplexity-webui-scraper:mcp

# Run MCP server (requires token)
podman run --rm -e PERPLEXITY_SESSION_TOKEN=your_token ghcr.io/henrique-coder/perplexity-webui-scraper:mcp

For local development, you can still build the provided container files:

podman build -t perplexity-api -f Containerfile .
podman run --rm -it -p 8000:8000 perplexity-api

podman build -t perplexity-mcp -f Containerfile.mcp .
podman run --rm -it -e PERPLEXITY_SESSION_TOKEN=your_token perplexity-mcp

CLI options

Option Short Default Description
--host -H 127.0.0.1 Bind address
--port -p 8000 Port to listen on
--reload False Enable auto-reload (dev)
--log-level info Uvicorn log level

Authentication

Pass your Perplexity session token as the API key in every request — exactly like the OpenAI API:

# curl
curl http://localhost:8000/v1/chat/completions \
  -H "Authorization: Bearer YOUR_SESSION_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"model": "perplexity/best", "messages": [{"role": "user", "content": "Hello!"}]}'

# Streaming
curl -N http://localhost:8000/v1/chat/completions \
  -H "Authorization: Bearer YOUR_SESSION_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"model": "perplexity/best", "messages": [{"role": "user", "content": "Hello!"}], "stream": true}'
from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:8000/v1",
    api_key="YOUR_SESSION_TOKEN",  # sent as Authorization: Bearer automatically
)

response = client.chat.completions.create(
    model="perplexity/best",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

API endpoints

Method Path Description
GET /v1/models List all available models
POST /v1/chat/completions Chat completion (streaming + non-streaming)
GET /docs Interactive Swagger UI
GET /redoc ReDoc documentation

Fields not supported by Perplexity (e.g. temperature, top_p) are accepted for client compatibility but silently ignored.

MCP Server

Expose every Perplexity model as a separate tool for AI agents (Claude Desktop, Antigravity, etc.):

{
  "mcpServers": {
    "perplexity-webui-scraper": {
      "command": "uvx",
      "args": [
        "--from",
        "perplexity-webui-scraper[mcp]@latest",
        "perplexity-webui-scraper",
        "mcp"
      ],
      "env": { "PERPLEXITY_SESSION_TOKEN": "your_token_here" }
    }
  }
}

See the full MCP documentation for all tools and configuration details.

Disclaimer

This is an unofficial library. It uses internal APIs that may change without notice. Use at your own risk. By using this library, you agree to Perplexity AI's Terms of Service.

About

An advanced, high-performance Python client, MCP server, and REST API for reverse-engineering Perplexity AI's WebUI.

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