Model Context Protocol

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Lightconetech

A gateway demo for MCP SSE Server

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RHuijts

A Model Context Protocol (MCP) server that provides access to the Rijksmuseum's collection through natural language interactions. This server enables AI models to explore, analyze, and interact with artworks and collections from the Rijksmuseum.

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Jsonallen

A Model Context Protocol (MCP) server that provides web search functionality using Perplexity AI's API. Works with the Anthropic Claude desktop client.

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MetoroIocloud

Write Model Context Protocol servers in few lines of go code. Docs at https://mcpgolang.com

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Strowkcloud

Foxy contexts is a Golang library for building context servers supporting Model Context Protocol.

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Punkpeyecloud

A TypeScript framework for building MCP servers.

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Jlowincloud

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

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KsGenAicloud

A TypeScript-based MCP server that provides tools to interact with Confluence. It demonstrates core MCP concepts.

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Mindscapehqcloud

MCP Server for Raygun's API V3 endpoints for interacting with your Crash Reporting and Real User Monitoring applications. This server provides comprehensive access to Raygun's API features through the Model Context Protocol.

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Briandconnellycloud

IP Geolocation Server for MCP

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Mark3labscloud

Go server implementing Model Context Protocol (MCP) for filesystem operations.

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.