Sponsored by Deepsite.site

Munin Ai Memory

Created By
kaleraa month ago
Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: - **Multi-Project Support:** Isolate memories into separate "brains" (Context Cores). - **GraphRAG:** Automatically builds a knowledge graph from your context. - **Sub-200ms Search:** Blazing fast Hybrid & Semantic search. - **Privacy:** Zero-knowledge client-side encryption (E2EE) support. - **Pricing:** FREE FOREVER for the base tier (Pro and Elite Plan start from $1.6/m).
Overview

🧠 Munin Ecosystem for AI Agents

Status: Active Powered by: GraphRAG Protocol: MCP License: MIT

Give your AI Agents a robust, Long-Term Memory.

Have you ever been frustrated when your AI agent forgets the architectural decisions you made yesterday? Or when it repeats the exact same bug it fixed in the previous session?

Munin is a Full-Stack Long-Term Memory manager powered by GraphRAG. This monorepo contains the official Model Context Protocol (MCP) adapters and SDKs to connect Munin Context Cores to your favorite AI tools—allowing them to build, query, and maintain a persistent knowledge graph of your entire project across endless sessions.


✨ Feature Highlights

Munin isn't just a database; it's a cognitive layer for your AI agents:

  • 🛡️ AI Memory Guard: Detects semantic contradictions in your agent's memory to ensure consistency.
  • 🕸️ GraphRAG Visualizer: Auto-extracts entities and relationships into interactive 2D neural knowledge graphs and Mermaid-compatible diagrams.
  • Lower Token Costs: Semantic hybrid search (Vector + Keyword) ensures agents pull only the most relevant snippets, keeping prompts lean and fast.
  • 🔐 E2EE With GraphRAG: Industry-leading security. Encrypt your memory end-to-end while maintaining the ability to perform high-performance semantic search (Elite Tier).
  • 🕒 Temporal Search: Search by time context—ask "what did we decide last Tuesday?" and get exact answers.
  • 📌 Dynamic Pinning: Force-inject critical project context (like coding standards or core architecture) so AI never loses the "big picture".
  • 🤝 Cross-Project Sharing: Share selected memories across different projects to reuse logic and context without manual copy-pasting.
  • Memory TTL: Set expiration windows for temporary context to keep your memory cores clean and noise-free.

🔌 Supported Adapters

This ecosystem provides first-class, plug-and-play MCP adapters for the most popular AI development tools. Choose your platform to get started:


📦 Monorepo Structure

This repository is organized as a pnpm workspace containing the core SDKs, the protocol specification, and all individual adapters:

  • Protocol Spec: packages/spec
  • TypeScript SDK: packages/ts-sdk
  • Python SDK: packages/python-sdk
  • First-Class Adapters: adapters/*
  • Generic MCP Template: adapters/generic-mcp-template
  • Contract Test Harness: tests/contract
  • Release Tag Mapping: docs/release-tags.md

🛠️ Developer Guide

If you are contributing to the Munin Ecosystem, use the following commands to manage the monorepo.

Quick Commands

pnpm install
pnpm lint
pnpm build
pnpm test
pnpm test:contract

Contract Test

Start the mock server (default 4010):

pnpm test:contract:mock

If the port is occupied, run on another port:

MUNIN_CONTRACT_PORT=4011 pnpm test:contract:mock
MUNIN_CONTRACT_PORT=4011 pnpm test:contract

You can also override the full base URL directly:

MUNIN_CONTRACT_BASE_URL=http://127.0.0.1:4011 pnpm test:contract

By default, the contract runner uses:

  • tests/contract/adapter-manifests/munin-sdk-local.json

Override with a custom manifest:

pnpm test:contract -- tests/contract/adapter-manifests/<manifest>.json

Built with ❤️ by Kalera for the AI Engineering community.

Server Config

{
  "mcpServers": {
    "munin": {
      "command": "npx",
      "args": [
        "-y",
        "@kalera/munin-mcp-server"
      ],
      "env": {
        "MUNIN_API_KEY": "<YOUR_API_KEY>",
        "MUNIN_PROJECT_ID": "<YOUR_PROJECT_ID>"
      }
    }
  }
}
Recommend Servers
TraeBuild with Free GPT-4.1 & Claude 3.7. Fully MCP-Ready.
Amap Maps高德地图官方 MCP Server
MCP AdvisorMCP Advisor & Installation - Use the right MCP server for your needs
EdgeOne Pages MCPAn MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.
MiniMax MCPOfficial MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
ChatWiseThe second fastest AI chatbot™
Baidu Map百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Serper MCP ServerA Serper MCP Server
Playwright McpPlaywright MCP server
Jina AI MCP ToolsA Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.
Y GuiA web-based graphical interface for AI chat interactions with support for multiple AI models and MCP (Model Context Protocol) servers.
Tavily Mcp
CursorThe AI Code Editor
WindsurfThe new purpose-built IDE to harness magic
Howtocook Mcp基于Anduin2017 / HowToCook (程序员在家做饭指南)的mcp server,帮你推荐菜谱、规划膳食,解决“今天吃什么“的世纪难题; Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"
DeepChatYour AI Partner on Desktop
BlenderBlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.
AiimagemultistyleA Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.
RedisA Model Context Protocol server that provides access to Redis databases. This server enables LLMs to interact with Redis key-value stores through a set of standardized tools.
Zhipu Web SearchZhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.
Visual Studio Code - Open Source ("Code - OSS")Visual Studio Code