Dragon Brain

v1.0.0Knowledge & Memorystable

Dragon Brain — persistent long-term memory for AI agents via MCP (Model Context Protocol). Knowledge graph (FalkorDB) + vector search (Qdrant) + CUDA GPU embeddings. Works with Claude, Gemini CLI, Cursor, Windsurf, VS Code Copilot. 30 tools, 1121 tes

ai-memoryclaudecodex-clicursorfalkordb
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What is Dragon Brain?

Dragon Brain is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to dragon brain — persistent long-term memory for ai agents via mcp (model context protocol). knowledge graph (falkordb) + vector search (qdrant) + cuda gpu embeddings. works with claude, gemini cli, cur...

Dragon Brain — persistent long-term memory for AI agents via MCP (Model Context Protocol). Knowledge graph (FalkorDB) + vector search (Qdrant) + CUDA GPU embeddings. Works with Claude, Gemini CLI, Cursor, Windsurf, VS Code Copilot. 30 tools, 1121 tes

This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Dragon Brain — persistent long-term memory for AI agents via

Use Cases

Store persistent long-term memory with knowledge graphs
Enable AI agents to retrieve contextual information across sessions
iikarus

Maintainer

LicenseMIT
Languagepython
Versionv1.0.0
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx dragon-brain

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Dragon Brain

Dragon Brain is a production-grade persistent memory MCP server for AI agents, combining a FalkorDB knowledge graph with Qdrant vector search and BGE-M3 embeddings to achieve 100% recall@5 on the LongMemEval benchmark. It exposes 34 MCP tools covering entity storage, semantic search, relationship traversal, time-travel queries, and autonomous memory clustering — all without requiring an LLM for retrieval. Works with Claude Code, Claude Desktop, Cursor, Windsurf, Gemini CLI, and any MCP-compatible client.

Prerequisites

  • Docker and Docker Compose installed
  • Python 3.12 or higher (if using the pip package instead of Docker-only mode)
  • An MCP-compatible client such as Claude Code, Claude Desktop, or Cursor
  • NVIDIA GPU with CUDA drivers (optional, for GPU-accelerated embeddings)
1

Start the backend services with Docker Compose

Dragon Brain requires four Docker containers: FalkorDB (knowledge graph on port 6379), Qdrant (vector search on port 6333), an Embedding API serving BGE-M3 on port 8001, and a Streamlit dashboard on port 8501. Start them all with one command.

# CPU mode (default)
docker compose up -d

# GPU mode (NVIDIA CUDA)
docker compose --profile gpu up -d
2

Verify all containers are healthy

Check that all four containers are running before connecting your MCP client.

docker ps --filter "name=claude-memory"
3

Install the MCP server package

Install the dragon-brain Python package which provides the MCP server binary.

pip install dragon-brain
4

Connect Claude Code (recommended method)

Register Dragon Brain with Claude Code using the mcp add command.

claude mcp add dragon-brain -- python -m claude_memory.server
5

Add to Claude Desktop or other MCP clients

For Claude Desktop or other clients, add the server configuration with the service connection environment variables.

{
  "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"
      }
    }
  }
}
6

Start storing and retrieving memories

Tell your AI assistant to remember things. Dragon Brain creates typed entities, observations, and relationships in the knowledge graph and indexes them for semantic search across all future sessions.

Dragon Brain Examples

Client configuration

Claude Desktop configuration for Dragon Brain with local Docker services.

{
  "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"
      }
    }
  }
}

Prompts to try

Example prompts to store and retrieve memories using Dragon Brain's 34 tools.

- "Remember that I'm building Atlas in Rust and I prefer functional patterns"
- "What do you know about my projects?"
- "What relationships connect Project Atlas to distributed systems in your memory?"
- "What did you know about my preferences last Tuesday?"
- "Find all entities related to machine learning in my memory graph"
- "Search my memories for anything about database architecture"

Troubleshooting Dragon Brain

Docker containers fail to start or show as unhealthy

Run `docker compose logs` to see per-container errors. Common causes: port 6379 or 6333 already in use by another service, or insufficient Docker memory allocation (increase to at least 4GB in Docker Desktop settings).

Embedding API container is slow or times out

The BGE-M3 embedding model (~1GB) downloads on first start. Wait for the container to finish pulling and initializing before sending requests. Check progress with `docker logs claude-memory-embedding-1`.

claude mcp add succeeds but the server doesn't appear in Claude Code

Ensure the Docker services are running first (`docker compose up -d`) before starting Claude Code. Dragon Brain's server fails loudly if FalkorDB or Qdrant are unreachable — check that all four containers are healthy.

Frequently Asked Questions about Dragon Brain

What is Dragon Brain?

Dragon Brain is a Model Context Protocol (MCP) server that dragon brain — persistent long-term memory for ai agents via mcp (model context protocol). knowledge graph (falkordb) + vector search (qdrant) + cuda gpu embeddings. works with claude, gemini cli, cursor, windsurf, vs code copilot. 30 tools, 1121 tes It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Dragon Brain?

Follow the installation instructions on the Dragon Brain GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Dragon Brain?

Dragon Brain works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Dragon Brain free to use?

Yes, Dragon Brain is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More Knowledge & Memory MCP Servers

Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "dragon-brain": { "command": "npx", "args": ["-y", "dragon-brain"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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