Dragon Brain

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Memory infrastructure for AI agents — that fails loud, by design.

100% LongMemEval R@5 · 34 MCP tools · sub-200ms hybrid search · CI-gated fail-loud contracts · No LLM required

An open-source MCP server that gives any LLM long-term memory using a knowledge graph + vector search hybrid. Store entities, observations, and relationships — then recall them semantically across sessions. Works with any MCP client: Claude Code, Claude Desktop, Cursor, Windsurf, Cline, Gemini CLI, VS Code Copilot, or any LLM that speaks Model Context Protocol.

Unlike flat chat history or simple RAG, Dragon Brain understands relationships between memories — not just similarity. An autonomous agent ("The Librarian") periodically clusters and synthesizes memories into higher-order concepts.

And it tells you when it can't remember — instead of pretending the memory was never there. (why this matters →)

Quick Start

Prerequisites: Docker and Docker Compose. Detailed setup: See docs/SETUP.md for comprehensive instructions including prerequisites, platform-specific notes, and troubleshooting.

1. Start the Services

docker compose up -d

This spins up 4 containers:

• FalkorDB (knowledge graph) — port 6379
• Qdrant (vector search) — port 6333
• Embedding API (BGE-M3, CPU default) — port 8001
• Dashboard (Streamlit) — port 8501

GPU users: docker compose --profile gpu up -d for NVIDIA CUDA acceleration.

Verify everything is healthy:

docker ps --filter "name=claude-memory"

Alternative: Install via pip

pip install dragon-brain

Note: Dragon Brain requires FalkorDB and Qdrant running as Docker services. The pip package installs the MCP server — run docker compose up -d first for the infrastructure. The embedding model (~1GB) is served via Docker, not downloaded locally.

2. Connect Your AI Agent

Claude Code (recommended):

claude mcp add dragon-brain -- python -m claude_memory.server

Claude Desktop / Other MCP Clients

Add to your MCP client config:

{
  "mcpServers": {
    "dragon-brain": {
      "command": "python",
      "args": ["-m", "claude_memory.server"],
      "env": {
        "FALKORDB_HOST": "localhost",
        "FALKORDB_PORT": "6379",
        "QDRANT_HOST": "localhost",
        "QDRANT_PORT": "6333",
        "EMBEDDING_API_URL": "http://localhost:8001"
      }
    }
  }
}

See mcp_config.example.json for a full template. This server works with any MCP-compatible client via stdio transport.

3. Start Remembering

You: "Remember that I'm building Atlas in Rust and I prefer functional patterns."
AI:  [creates entity "Atlas", adds observations about Rust and functional patterns]

You (next session): "What do you know about my projects?"
AI:  "You're building Atlas in Rust with a functional approach..." [recalled from graph]

What It Does