Memgraph MCP Server

What is Memgraph MCP Server?

Enables Memgraph to receive and execute Cypher queries from LLMs via the Model Context Protocol, exposing query and schema endpoints as tools for AI agents.

How to use Memgraph MCP Server?

1. Install uv (a fast Python package manager).2. Create and activate a virtual environment: uv venv && .venv\Scripts\activate (Linux/macOS: source .venv/bin/activate).3. Install dependencies: uv add "mcp[cli]" httpx.4. Start the server: uv run server.py.
2. (Optional) Configure Claude Desktop or any MCP‑compatible client to point to the running server.
3. Run Memgraph MAGE container with schema info enabled:

   docker run -p 7687:7687 memgraph/memgraph-mage --schema-info-enabled=True
   

Key Features

• run_query() – Execute arbitrary Cypher queries against Memgraph.
• get_schema() – Retrieve full schema information when Memgraph is started with --schema-info-enabled=True.
• Minimal Python footprint; runs with a single server.py script.
• Compatible with Claude Desktop and any MCP‑compliant client.
• Quick start video and step‑by‑step documentation.

Use Cases

• Augmenting LLM agents with real‑time graph data for intelligent reasoning.
• Building AI‑driven chatbots that can query and modify a graph database.
• Prototyping graph‑centric RAG (Retrieval‑Augmented Generation) pipelines.
• Enabling LangChain or LlamaIndex agents to interact with Memgraph without custom adapters.

FAQ

Q: Do I need a Memgraph license?
A: The server works with both the open‑source community edition and the enterprise edition of Memgraph.

Q: Which ports does the server listen on?
A: By default it uses the port defined by the underlying MCP library (commonly 8000); you can adjust it via environment variables in the server script.

Q: Can I run the server in production?
A: Yes, but for production you should containerize the server, enable TLS, and manage the virtual environment with a process manager.

Q: Is there a TypeScript version?
A: A TypeScript implementation is planned for a future release and will be part of the Memgraph AI Toolkit monorepo.

[!IMPORTANT]
This repository has been merged into the Memgraph AI Toolkit monorepo to avoid duplicating tools.
It will be deleted in one month—please follow the MCP integration there for all future development, and feel free to open issues or PRs in that repo.

🚀 Memgraph MCP Server

Memgraph MCP Server is a lightweight server implementation of the Model Context Protocol (MCP) designed to connect Memgraph with LLMs.

⚡ Quick start

📹 Memgraph MCP Server Quick Start video

1. Run Memgraph MCP Server

1. Install uv and create venv with uv venv. Activate virtual environment with .venv\Scripts\activate.
2. Install dependencies: uv add "mcp[cli]" httpx
3. Run Memgraph MCP server: uv run server.py.

2. Run MCP Client

1. Install Claude for Desktop.
2. Add the Memgraph server to Claude config:

MacOS/Linux

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows

code $env:AppData\Claude\claude_desktop_config.json

Example config:

{
    "mcpServers": {
      "mpc-memgraph": {
        "command": "/Users/katelatte/.local/bin/uv",
        "args": [
            "--directory",
            "/Users/katelatte/projects/mcp-memgraph",
            "run",
            "server.py"
        ]
     }
   }
}

[!NOTE]
You may need to put the full path to the uv executable in the command field. You can get this by running which uv on MacOS/Linux or where uv on Windows. Make sure you pass in the absolute path to your server.

3. Chat with the database

1. Run Memgraph MAGE:

   docker run -p 7687:7687 memgraph/memgraph-mage --schema-info-enabled=True
   

   The --schema-info-enabled configuration setting is set to True to allow LLM to run SHOW SCHEMA INFO query.
2. Open Claude Desktop and see the Memgraph tools and resources listed. Try it out! (You can load dummy data from Memgraph Lab Datasets)

🔧Tools

run_query()

Run a Cypher query against Memgraph.

🗃️ Resources

get_schema()

Get Memgraph schema information (prerequisite: --schema-info-enabled=True).

🗺️ Roadmap

The Memgraph MCP Server is just at its beginnings. We're actively working on expanding its capabilities and making it even easier to integrate Memgraph into modern AI workflows. In the near future, we'll be releasing a TypeScript version of the server to better support JavaScript-based environments. Additionally, we plan to migrate this project into our central AI Toolkit repository, where it will live alongside other tools and integrations for LangChain, LlamaIndex, and MCP. Our goal is to provide a unified, open-source toolkit that makes it seamless to build graph-powered applications and intelligent agents with Memgraph at the core.