FalkorDB FalkorDB MCPServer

FalkorDB FalkorDB MCPServer avatar

by FalkorDB

FalkorDB MCP Server

What is FalkorDB FalkorDB MCPServer

FalkorDB MCP Server

A Model Context Protocol (MCP) server for FalkorDB, allowing AI models to query and interact with graph databases.

Overview

This project implements a server that follows the Model Context Protocol (MCP) specification to connect AI models with FalkorDB graph databases. The server translates and routes MCP requests to FalkorDB and formats the responses according to the MCP standard.

Prerequisites

  • Node.js (v16 or later)
  • npm or yarn
  • FalkorDB instance (can be run locally or remotely)

Installation

  1. Clone this repository:

    git clone https://github.com/falkordb/falkordb-mcpserver.git
    cd falkordb-mcpserver
    
  2. Install dependencies:

    npm install
    
  3. Copy the example environment file and configure it:

    cp .env.example .env
    

    Edit .env with your configuration details.

Configuration

Configuration is managed through environment variables in the .env file:

  • PORT: Server port (default: 3000)
  • NODE_ENV: Environment (development, production)
  • FALKORDB_HOST: FalkorDB host (default: localhost)
  • FALKORDB_PORT: FalkorDB port (default: 6379)
  • FALKORDB_USERNAME: Username for FalkorDB authentication (if required)
  • FALKORDB_PASSWORD: Password for FalkorDB authentication (if required)
  • MCP_API_KEY: API key for authenticating MCP requests

Usage

Development

Start the development server with hot-reloading:

npm run dev

Production

Build and start the server:

npm run build
npm start

API Endpoints

  • GET /api/mcp/metadata: Get metadata about the FalkorDB instance and available capabilities
  • POST /api/mcp/context: Execute queries against FalkorDB
  • GET /api/mcp/health: Check server health
  • GET /api/mcp/graphs: Returns the list of Graphs

MCP Configuration

To use this server with MCP clients, you can add it to your MCP configuration:

{
  "mcpServers": {
    "falkordb": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-p", "3000:3000",
        "--env-file", ".env",
        "falkordb-mcpserver",
        "falkordb://host.docker.internal:6379"
      ]
    }
  }
}

For client-side configuration:

{
  "defaultServer": "falkordb",
  "servers": {
    "falkordb": {
      "url": "http://localhost:3000/api/mcp",
      "apiKey": "your_api_key_here"
    }
  }
}

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.

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