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This repository contains implementations of the Model Context Protocol (MCP), an open standard that connects AI systems with external tools and data sources.

Обзор

This repository contains implementations of the Model Context Protocol (MCP), an open standard that connects AI systems with external tools and data sources.

README

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MCP (Model Context Protocol)

This repository contains implementations of the Model Context Protocol (MCP), an open standard that connects AI systems with external tools and data sources.

About IgnitionAI

IgnitionAI is an open-source organization dedicated to advancing AI capabilities through accessible and collaborative tools. We believe in the power of community-driven development to create robust, ethical, and innovative AI solutions.

Repository Contents

This is a monorepo containing multiple MCP server implementations:

  • azure-storage-mcp: Complete Azure Storage integration with Table Storage, Blob Storage, Service Bus Queues, and Storage Queues
  • azure-ai-search: Azure AI Search integration (in development)
  • linkedin-mcp: LinkedIn API integration with OAuth authentication
  • linkedin-mcp-http: HTTP variant of LinkedIn MCP server
  • fit-mcp: MCP implementation for fitness and nutrition calculations
  • node-mcp: Simple Node.js MCP implementation
  • mcp-template: Base template for creating new MCP servers

Development

Prerequisites

  • Node.js and pnpm
  • Service-specific credentials (see individual server documentation)

Commands

  • pnpm build - Build all projects
  • pnpm start - Start development server
  • pnpm start:prod - Start production server
  • pnpm inspect - Run MCP inspector for debugging
  • docker compose up -d - Start LinkedIn HTTP server

About MCP

The Model Context Protocol (MCP) is a standard that enables AI models to interact with external tools, APIs, and services, extending their capabilities beyond their initial training. These repositories are available for everyone to use, modify, and contribute to.

Configuration Examples

Azure Storage MCP

"azure-storage": {
  "command": "npx",
  "args": ["azure-storage-mcp"],
  "env": {
    "AZURE_STORAGE_CONNECTION_STRING": "your-connection-string"
  }
}

Azure AI Search MCP

"azure-ai-search": {
  "command": "npx",
  "args": ["azure-ai-search-mcp"],
  "env": {
    "AZURE_SEARCH_ENDPOINT": "your-search-endpoint",
    "AZURE_SEARCH_API_KEY": "your-api-key"
  }
}

LinkedIn MCP

"linkedin": {
  "command": "npx",
  "args": ["-y", "linkedin-mcp"],
  "env": {
    "LINKEDIN_CLIENT_ID": "your-client-id",
    "LINKEDIN_CLIENT_SECRET": "your-client-secret",
    "LINKEDIN_REDIRECT_URI": "your-redirect-uri"
  }
}

Fit MCP

"fit-mcp": {
  "command": "npx",
  "args": ["fitmcp"]
}

How to Get LinkedIn API Keys

To obtain the necessary LinkedIn API credentials (LINKEDIN_CLIENT_ID, LINKEDIN_CLIENT_SECRET, and LINKEDIN_REDIRECT_URI), follow these steps:

  1. Create a LinkedIn Developer Account
    Visit LinkedIn Developer Portal and log in with your LinkedIn account.

  2. Create a New App
    Click Create app, fill out the required details, and submit.

  3. Get Client ID and Client Secret

Открыть полный README на GitHub

Установка

npx azure-storage-mcp
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