iflow-mcp_kayacancode-infinite-context-mcp

# Unified Context Layer MCP A Memory System for AI assistants that goes beyond traditional RAG. Store conversations, build knowledge graphs, extract facts, and maintain user profiles—all searchable with semantic understanding.Use across your apps and LLMs. ## Features ### Core Memory - **Infinite Context** - Automatically compress long conversations while preserving important information - **Vector Search** - Semantic search across all saved conversations using Pinecone - **Full Content Storage** - Store up to ~5,000 words per chunk with formatting preserved - **Smart Compression** - LLM-powered intelligent summarization ### Memory System - **User Profiles** - Automatically learns your interests, projects, and preferences - **Entity Graphs** - Build knowledge graphs connecting people, projects, concepts - **Fact Extraction** - Extract and chain atomic facts from conversations - **Temporal Awareness** - Understand recency and relevance over time - **Hybrid Scoring** - Combine semantic similarity with temporal and entity signals ### Query Understanding - **Query Classification** - Understand intent (search, save, question, etc.) - **Query Rewrites** - Generate synonyms, broader terms, and expansions - **Enhanced Search** - Guardrails, auto-refinement, and follow-up recommendations ### Indexing - **GitHub Repositories** - Index entire repos for code search - **Documentation Sites** - Crawl and index docs - **Websites** - Full website crawling - **Local Filesystems** - Index local directories - **Single URLs** - Index individual pages (blogs, ChatGPT conversations, tweets) --- ## 🚀 Quick Start ### 1. Clone the Repository ```bash git clone https://github.com/yourusername/infinite-context-mcp.git cd infinite-context-mcp ``` ### 2. Create Virtual Environment ```bash python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate ``` ### 3. Install Dependencies ```bash pip install -r requirements.txt ``` ### 4. Configure API Keys ```b…