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MCP Servers Collection

by melkorCBA

This repository contains a collection of custom MCP (Model Context Protocol) servers that enhance AI capabilities with specialized services. These servers allow AI assistants to access real-time information and perform actions.

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What is MCP Servers Collection?

This is a collection of Model Context Protocol (MCP) servers designed to extend the capabilities of AI systems. MCP enables AI systems to interact with external services, providing access to real-time information and enabling them to perform actions.

How to use MCP Servers Collection?

To use these servers, clone the repository, navigate to the desired server's directory, follow the setup instructions in its README, and connect your AI assistant to the running MCP server. Ensure you have Node.js 18+, pnpm, and any required API keys.

Key features of MCP Servers Collection

  • Extends AI capabilities beyond static training data

  • Enables AI systems to interact with external services

  • Provides access to real-time information

  • Allows AI assistants to perform actions

  • Includes individual servers with dedicated READMEs and setup instructions

Use cases of MCP Servers Collection

  • Enhancing AI assistants with real-time data

  • Enabling AI systems to perform actions through external services

  • Creating specialized AI services with custom functionalities

  • Integrating AI with external APIs and data sources

FAQ from MCP Servers Collection

What is MCP?

Model Context Protocol (MCP) enables AI systems to interact with external services.

What are the setup requirements?

Most servers require Node.js 18+, pnpm package manager, and API keys (if the server connects to external services).

How do I contribute?

Feel free to contribute by adding new MCP servers or enhancing existing ones through pull requests.

Where can I find setup instructions?

Each MCP server is contained in its own directory with a dedicated README and setup instructions.

Are there any environment variables required?

Some servers require environment variables for API access. Check each server's directory for a .env.example file detailing required variables.