Model Context Protocol

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by Tag: Claude

Jlowin logo
Jlowin

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

Secretiveshell logo
Secretiveshell

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

Jsonallen logo
Jsonallen

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

idosal logo
idosal

Put an end to code hallucinations! GitMCP is a free, open-source, remote MCP server for any GitHub project

G0t4 logo
G0t4

Model Context Protocol server to run commands

Lightconetech logo
Lightconetech

A gateway demo for MCP SSE Server

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claude-task-master

2 weeks ago
eyaltoledano logo
eyaltoledano

An AI-powered task-management system you can drop into Cursor, Lovable, Windsurf, Roo, and others.

GitMCP

2 weeks ago
idosal logo
idosal

Put an end to code hallucinations! GitMCP is a free, open-source, remote MCP server for any GitHub project

upstash logo
upstash

Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors

Filtering by tag:Claude
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Andybrandt logo
AndybrandtΒ·cloud

MCP server that gives Claude ability to use OpenAI's GPTs assistants

Danhilse logo
DanhilseΒ·cloud

A simple MCP integration that allows Claude to read and manage a personal Notion todo list. This is a basic implementation tailored specifically for a minimalist todo list setup in Notion.

Jsonallen logo
JsonallenΒ·cloud

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

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.