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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 projectspnpm start- Start development serverpnpm start:prod- Start production serverpnpm inspect- Run MCP inspector for debuggingdocker 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:
-
Create a LinkedIn Developer Account
Visit LinkedIn Developer Portal and log in with your LinkedIn account. -
Create a New App
Click Create app, fill out the required details, and submit. -
Get Client ID and Client Secret
Установка
npx azure-storage-mcp