Model Context Protocol

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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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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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Ferrislucas

A Model Context Protocol server that executes commands in the current iTerm session - useful for REPL and CLI assistance

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Punkpeye

A TypeScript framework for building MCP servers.

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Hannesrudolph·cloud

An MCP server that provides safe access to your iMessage database through Model Context Protocol (MCP). This server is built with the FastMCP framework and the imessagedb library, enabling LLMs to query and analyze iMessage conversations with proper phone number validation and attachment handling.

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Joshuarileydev·on-premise

A Model Context Protocol (MCP) server that provides programmatic control over iOS simulators. This server implements the MCP specification to expose simulator functionality through a standardized interface.

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Ferdousbhai·cloud

A Model Context Protocol server for building an investor agent

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Ferrislucas·cloud

A Model Context Protocol server that executes commands in the current iTerm session - useful for REPL and CLI assistance

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Manusa·cloud

Model Context Protocol (MCP) server for Kubernetes and OpenShift

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.