doobidoo/mcp-memory-service
Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowledge graph + autonomous consolidation.
What it solves
AI agents typically suffer from "amnesia," losing all context and project history once a session ends. This project provides a persistent, shared memory backend that allows agents to store decisions, code patterns, and architecture context, ensuring that new sessions start with existing knowledge rather than from zero.
How it works
It operates as a self-hosted service that can be accessed via a REST API or the Model Context Protocol (MCP). It uses AI embeddings (run locally via ONNX) for semantic search and supports multiple storage backends including SQLite, Milvus, and Cloudflare. The system organizes information as a knowledge graph with typed edges to track causal relationships between facts, rather than just storing isolated snippets of text.
Who it’s for
Developers building agentic pipelines with frameworks like LangGraph, CrewAI, or AutoGen, as well as users of MCP-compatible clients like Claude Desktop, Cursor, and Windsurf who want their AI assistants to remember details across different chats and tools.
Highlights
- Multi-Transport Support: Accessible via REST API, MCP, and a web dashboard.
- Knowledge Graph: Visualizes and manages memories as an interactive 3D galaxy of nodes and relationships.
- Local-First Privacy: Embeddings run locally via ONNX to keep data within your own infrastructure.
- Framework Agnostic: Works with any HTTP client and integrates with major AI IDEs and desktop apps.
- Flexible Backends: Supports local SQLite for speed, Milvus for dedicated vector search, and Cloudflare for team synchronization.
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