Model Context Protocol

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Jlowin

The fast, Pythonic way to build Model Context Protocol servers πŸš€

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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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Pyroprompts logo
PyropromptsΒ·cloud

Integrate Claude with Any OpenAI SDK Compatible Chat Completion API - OpenAI, Perplexity, Groq, xAI, PyroPrompts and more. This is a TypeScript-based MCP server that implements an implementation into any OpenAI SDK Compatible Chat Completions API.

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SirmewsΒ·cloud

Read your Apple Notes with Claude Model Context Protocol

Hmk logo
HmkΒ·cloud

This is an MCP server for Attio, the AI-native CRM. It allows mcp clients (like Claude) to connect to the Attio API.

Hmk logo
HmkΒ·cloud

A Box model context protocol server to search, read and access files

Chronulusai logo
ChronulusaiΒ·cloud

MCP Server for Chronulus AI Forecasting and Prediction Agents

Jasonjmcghee logo
JasonjmcgheeΒ·cloud

Enable any LLM (e.g. Claude) to interactively debug any language for you via MCP and a VS Code Extension

MarimoTeam logo
MarimoTeamΒ·cloud

CodeMirror extension to hook up a Model Context Provider (MCP)

Topoteretes logo
TopoteretesΒ·cloud

Reliable LLM Memory for AI Applications and AI Agents

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.