mcp-memory-service

Persistent Shared Memory for AI Agent Pipelines

Open-source memory backend for AI agents — REST API, MCP, OAuth, CLI, dashboard. One self-hosted service, every transport. Agents store decisions, share causal knowledge graphs, and retrieve context in 5ms — without cloud lock-in or API costs.

Works with LangGraph · CrewAI · AutoGen · any HTTP client · Claude Desktop · OpenCode

▶ The 3D knowledge graph in motion — every memory a glowing node, every relationship a curved edge.

Why Agents Need This

Your AI assistant forgets everything when you start a new chat. You spend 10 minutes re-explaining your architecture. Again. MCP Memory Service captures project context, architecture decisions, and code patterns automatically — new sessions start with everything already known.

Key capabilities for agent pipelines:

• Framework-agnostic REST API — no MCP client library needed; the live endpoint list is at /api/docs
• Knowledge graph — agents share causal chains, not just facts
• X-Agent-ID header — auto-tag memories by agent identity for scoped retrieval
• conversation_id — bypass deduplication for incremental conversation storage
• SSE events — real-time notifications when any agent stores or deletes a memory
• Embeddings run locally via ONNX — memory never leaves your infrastructure

🚀 Get Started in 60 Seconds

Not sure which setup fits? The Setup Guide walks you to the right path in under a minute.

1. Install:

pip install mcp-memory-service

2. Configure your AI client:

{
  "mcpServers": {
    "memory": {
      "command": "memory",
      "args": ["server"]
    }
  }
}

claude mcp add memory -- memory server

MCP_ALLOW_ANONYMOUS_ACCESS=true memory server --http
# REST API running at http://localhost:8000

MCP_ALLOW_ANONYMOUS_ACCESS=true memory server --http

git clone https://github.com/doobidoo/mcp-memory-service.git
cd mcp-memory-service
python scripts/installation/install.py

⚡ Works With Your Favorite AI Tools

• Agent frameworks (REST): LangGraph · CrewAI · AutoGen · OpenClaw/Nanobot · any HTTP client
• CLI and terminal (MCP): Claude Code · Gemini CLI · OpenCode · Codex CLI · Goose · Aider · Amp
• Desktop and IDE (MCP): Claude Desktop · VS Code · Cursor · Windsurf · Raycast · JetBrains · Zed
• Chat (MCP): ChatGPT (Developer Mode) · claude.ai (Remote MCP over HTTPS)

Full list, plus clients without OAuth such as Home Assistant: docs/integrations.md

✨ Features

🧠 Persistent Memory – Context survives across sessions with semantic search 🔍 Smart Retrieval – Finds relevant context automatically using AI embeddings ⚡ 5ms Speed – Instant context injection, no latency ☁️ Cloud Sync – Optional Cloudflare backend for team collaboration 🔒 Privacy-First – Local-first, you control your data 📊 Web Dashboard – Visualize and manage memories at http://localhost:8000 🧬 Knowledge Graph – Interactive D3.js visualization of memory relationships 🏠 Homelab Quality Scoring – Point scoring at any OpenAI-compatible endpoint (Ollama, LiteLLM, vLLM) 🔗 Entity Extraction – Auto-links @mentions, #tags, URLs, and file paths to a queryable entity graph 💡 Insight Cards – Consolidation surfaces patterns, trends, and knowledge gaps as structured insights 🏷️ Tag Match Filtering – tag_match=AND/OR on memory_search for precise multi-tag queries

The dashboard has eight tabs — Dashboard, Search, Browse, Documents, Manage, Analytics, Quality, API Docs. Two-minute walkthrough on YouTube · Web Dashboard Guide

How it compares to Mem0, Zep and the MCP-native alternatives, benchmark results, and deployments people run in production: mcpmemory.services

🛠️ Configuration Highlights

memory launch                  # Start HTTP server in background (127.0.0.1:8000)
memory launch --port 8192      # Custom port
memory info                    # Status and health
memory logs --lines 50         # Recent logs
memory stop                    # Stop server

These commands are optimized for fast startup and avoid loading heavy ML dependencies unless needed.

⚠️ Security note: the server binds to 127.0.0.1 (localhost only) by default. --host 0.0.0.0 / MCP_HTTP_HOST=0.0.0.0 exposes the API to your network — do that only in trusted environments with authentication and firewall rules, or behind TLS termination or a VPN overlay.

Backends, embedding models, quality scoring and every environment variable: Configuration Guide

📚 Documentation

• Setup Guide – Decision tree and step-by-step paths
• Agent Integration Guides – LangGraph, CrewAI, AutoGen, HTTP generic
• Remote MCP Setup – claude.ai and ChatGPT via HTTPS + OAuth
• Configuration Guide – Backend options and customization
• Architecture Overview – How it works under the hood
• Knowledge Graph Dashboard – Interactive graph visualization
• Benchmarks – LongMemEval, DevBench, LoCoMo, with run commands
• Migration Guide – Upgrading between major versions
• Troubleshooting – Common issues and solutions
• Wiki – Long-form guides and API reference
• Full documentation index – Everything else

Also listed on Glama and Spark.

📦 Releases

Every release, with upgrade notes: CHANGELOG.md · GitHub Releases · archived history

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines and SECURITY.md for reporting a vulnerability.

Who authors this project, who holds copyright, and what every change passes before it reaches main: AUTHORSHIP.md.

Quick Development Setup:

git clone https://github.com/doobidoo/mcp-memory-service.git
cd mcp-memory-service
pip install -e .  # Editable install
pytest tests/      # Run test suite

Supporting the Project

MCP Memory Service is maintained by one person. If it saves you or your company time, you can support its development via Ko-fi, Buy Me a Coffee or PayPal: SPONSORS.md.