Your eternal second brain, running locally. Private, fast, and built for AI agents that actually remember.
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# 🧠 Eternity MCP **Your Eternal Second Brain, Running Locally.** `Eternity MCP` is a lightweight, privacy-focused memory server designed to provide long-term memory for LLMs and AI agents using the Model Context Protocol (MCP). It combines structured storage (SQLite) with semantic vector search (ChromaDB), enabling agents to persist and retrieve text, PDF documents, and chat histories across sessions using natural language queries. Built to run fully locally, Eternity integrates seamlessly with MCP-compatible clients, LangChain, LangGraph, and custom LLM pipelines, giving agents a durable and private memory layer. --- ## 🚀 Why Eternity? Building agents that "remember" is hard. Most solutions rely on expensive cloud vector databases or complex setups. **Eternity** solves this by being: * **🔒 Private & Local**: Runs entirely on your machine. No data leaves your network. * **⚡ fast & Lightweight**: Built on FastAPI and ChromaDB. * **🔌 Agent-Ready**: Perfect for LangGraph, LangChain, or direct LLM integration. * **📄 Multi-Modal**: Ingests raw text and PDF documents automatically. * **🔎 Semantic Search**: Finds matches by *meaning*, not just keywords.  ## 📦 Installation You can install Eternity directly from PyPI (coming soon) or from source: ```bash # From source git clone https://github.com/danttis/eternity-mcp.git cd eternity ``` ## 🛠️ Usage ### 1. Start the Server Run the server in a terminal. It will host the API and the Memory UI. ```bash eternity ``` *Server runs at `http://localhost:8000`* ### 2. Client Usage (Python) You can interact with Eternity using simple HTTP requests. ```python import requests ETERNITY_URL = "http://localhost:8000" # 💾 Store a memory requests.post("{ETERNITY_URL}/add", data={ "content": "The project deadline is next Friday.", "tags": "work,deadline" }) # 🔍 Search memory response = requests.ge…
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