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framework-rai-mcp

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0 stars JavaScriptAI & Machine Learning Updated May 21, 2025

Documentation

Framework-RAI MCP Server

A Model Context Protocol (MCP) server for responsible AI development and documentation.

Features

  • Project Scanning: Automatically detect AI libraries, model files, and training scripts in your project
  • Responsible AI Suggestions: Generate suggestions for improving bias mitigation, transparency, privacy, and monitoring
  • Model Analysis: Analyze model code for potential issues related to bias, documentation, security, and testing
  • Documentation Management: Create and update responsible AI documentation including checklists and model cards

Installation

If you're using Cursor or another Smithery-compatible client, you can install this package directly:

bash
npx -y @smithery/cli@latest inspect @sebastianbuzdugan/framework-rai-mcp

When prompted by Smithery, you'll need to provide your OpenAI API key to use the AI-powered features.

Manual Installation

You can also install the package globally:

bash
npm install -g framework-rai-mcp

Or install locally for development:

bash
git clone https://github.com/sebastianbuzdugan/framework-rai-mcp.git
cd framework-rai-mcp
npm install

Usage

As a Smithery Plugin

Once installed via Smithery, the Framework-RAI functions will be available directly in your Smithery-compatible client like Cursor. The first time you use a function that requires OpenAI, you'll be prompted to enter your API key.

As a Command Line Tool

Start the MCP server:

bash
framework-rai-mcp

By default, the server runs on port 3001. You can specify a different port:

bash
framework-rai-mcp --port=3003

Setting Your OpenAI API Key

The AI-powered features require an OpenAI API key. You can provide it in several ways:

1. Command line argument:

bash
framework-rai-mcp --api-key=sk-your-openai-key

2. Environment variable:

bash
export OPENAI_API_KEY=sk-your-openai-key
   framework-rai-mcp

3. Create a .env file in your project directory:

code
OPENAI_API_KEY=sk-your-openai-key

JSON-RPC API

The server implements the Model Context Protocol (MCP) using JSON-RPC 2.0 at the `/mcp` endpoint. The following methods are available:

  • `initialize`: Initialize a session with the server
  • `tools/list`: List available tools
  • `tools/call`: Call a specific tool with parameters
  • `shutdown`: Terminate a session

Available Tools

  • `scanProject`: Scan a project for AI components
  • `generateSuggestions`: Generate responsible AI suggestions (requires OpenAI API key)
  • `analyzeModel`: Analyze a model file for potential issues (requires OpenAI API key)
  • `getDocumentation`: Get responsible AI documentation
  • `updateDocumentation`: Update responsible AI documentation

Testing the Server

You can test the server using the included test script:

bash
npm run mcp-test

This will send test requests to the server and display the responses.

Environment Variables

  • `PORT`: Port number for the server (default: 3001)
  • `OPENAI_API_KEY`: Your OpenAI API key (required for suggestions and analysis)

Requirements

  • Node.js 14 or higher
  • OpenAI API key (for AI-powered features)

License

MIT

Author

Sebastian Buzdugan

Frequently asked questions

What is framework-rai-mcp?

framework-rai-mcp is a Model Context Protocol (MCP) server listed in the TrackMCP directory.

How do I install framework-rai-mcp?

Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

Is framework-rai-mcp open source?

Yes — it is hosted on GitHub at https://github.com/sebastianbuzdugan/framework-rai-mcp.

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