context-optimization

AI context optimization platform for files, conversations, RAG, code, logs and AI agents with context compression, evidence preservation, content-addressed recovery and auditable Context Receipts.

Context intelligence layer for LLM agents: persistent memory with write-time dedup, sensitivity tagging, conflict detection, and hierarchical decay. ~12ms. No LLM calls. MIT.

Official Edgee CLI to interract with Edgee's Agent Gateway. Route Claude Code, Codex, Cursor, VS Code + Copilot, and more through Edgee's hosted gateway to cut token spend.

The open source, no-code MCP Server for AI-Native API Access

The Distillery. A Token Optimization Proxy

⚡ Cut Claude token usage by 90%+ — free, open-source, local-first context compression for Claude Code. Hybrid RAG (BM25 + ONNX vectors), AST chunking, reranking. No API needed.

Save context for what matters. The last agent you'll ever need.

💰 Save money on AI API costs! 76% token reduction, Auto-Fix token limits, Universal AI compatibility. Cline • Copilot • Claude • Cursor

Claude Code skill for optimizing oversized CLAUDE.md files using progressive disclosure

CodeGrok MCP is a Model Context Protocol (MCP) server that enables AI assistants to intelligently search and understand codebases using semantic embeddings and Tree-sitter parsing.

Your AI forgets everything between sessions. This fixes that — 98%+ retrieval accuracy, 100% on LongMemEval, 99% token savings. 44 MCP tools. Fully local, zero cost.

Context-Optimized Memory Bank — Reduce AI token usage with structured documentation and cache-aware reading strategies

Copilot Context Optimizer is a VS Code extension that gives GitHub Copilot specialized tools to analyze files and process terminal commands efficiently without overwhelming chat context. It extracts only specific information needed instead of dumping entire files or verbose outputs, keeping conversations focused on problem-solving.

MCP servers as CLI tools — built for AI agents

Lightweight, agent-optimized database CLI with one-shot schema introspection, column profiling, and ERD generation.

The Universal Open Knowledge Format (OKF) Ingestion Compiler. Convert PDF, DOCX, Markdown, and HTML into structured, cross-linked RAG context graphs using Google Gemini.

让 Agent 用最少的 token 做最准的事 — Token-efficient discipline for AI agents：压缩无效上下文/推理/输出，降低 token 消耗与响应延迟

This repository introduces the Letta framework, empowering developers to build LLM-based agents with long-term, persistent memory and advanced reasoning capabilities. It leverages concepts from MemGPT to optimize context usage and enable multi-agent collaboration for real-world applications like research, HR, and task management.

🎯 Optimize LLM token usage by 70-90% with smart context ranking, reducing costs while maintaining quality and performance.

GitHub Action that analyzes codebases and generates AI agent context documentation (CLAUDE.md/AGENTS.md) to optimize AI coding assistant efficiency. Reduces token waste and improves development velocity through intelligent recommendations.