Model Context Protocol

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Jlowin

The fast, Pythonic way to build Model Context Protocol servers 🚀

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Grafana

MCP server for Grafana

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Punkpeye

A TypeScript SSE proxy for MCP servers that use stdio transport.

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Sooperset

Model Context Protocol (MCP) server for Atlassian products (Confluence and Jira). This integration supports both Atlassian Cloud and Jira Server/Data Center deployments.

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Secretiveshell

A middleware to provide an openAI compatible endpoint that can call MCP tools

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LastmileAi

A simple, composable framework to build agents using Model Context Protocol and simple workflow patterns

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GithubBurtthecoder·cloud

A Model Context Protocol (MCP) server for querying the VirusTotal API. This server provides comprehensive security analysis tools with automatic relationship data fetching. It integrates seamlessly with MCP-compatible applications like Claude Desktop.

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Pskill9·cloud

A Model Context Protocol (MCP) server that enables free web searching using Google search results, with no API keys required.

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Pskill9·cloud

This MCP server provides a tool to download entire websites using wget. It preserves the website structure and converts links to work locally.

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RHuijts·cloud

MCP Server implementation for Xcode integration. This server acts as a bridge between Claude and your local Xcode development environment, enabling intelligent code assistance, project management, and automated development tasks.

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Anaisbetts·cloud

A Model-Context Protocol Server for YouTube. Uses `yt-dlp` to download subtitles from YouTube and connects it to claude.ai via Model Context Protocol.

Domdomegg logo
Domdomegg·cloud

Airtable Model Context Protocol Server, for allowing AI systems to interact with your Airtable bases

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Reeeeemo·cloud

Ancestry MCP server made with Python that allows interactability with .ged (GEDCOM) files

Understanding Model Context Protocol (MCP)

Model Context Protocol (MCP) is a groundbreaking open-source protocol developed by Anthropic that revolutionizes how AI systems interact with external data sources. As the foundation for next-generation AI interactions, MCP enables AI assistants like Claude to establish secure and standardized connections with various data sources and tools.

Key Features of MCP

  • Universal Standard: Provides a unified framework for AI systems to access external data, tools, and prompts
  • Client-Server Architecture: Implements a robust and scalable architecture for seamless AI interactions
  • Security-First Design: Ensures secure data transmission and access control between AI systems and data sources
  • Tool Integration: Enables AI assistants to interact with various external tools and services
  • Standardized Communication: Establishes consistent protocols for data exchange and interaction patterns

Benefits for AI Development

MCP represents a significant advancement in AI infrastructure, offering developers and organizations a standardized way to build and deploy AI applications. By providing a common protocol, MCP reduces implementation complexity and ensures compatibility across different AI systems and data sources.

Whether you're developing AI applications, managing data infrastructure, or implementing AI solutions, MCP provides the foundation for secure, efficient, and standardized AI interactions. Explore our directory to find MCP servers that match your specific needs and requirements.