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

Using Smithery (Recommended)

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

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:

npm install -g framework-rai-mcp

Or install locally for development:

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:

framework-rai-mcp

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

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:

Command line argument:

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

Environment variable:

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

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

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