Model Context Protocol
🔥 Top Viewed This Week
by Tag: Python
Search by server name, description, or features
Popular Tags
A knowledge graph server that uses the Model Context Protocol (MCP) to provide structured memory persistence for AI models. v0.2.8
Model Context Protocol Servers. This repository is a collection of reference implementations for the Model Context Protocol (MCP), demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources.
A C# SDK implementation of the Model Context Protocol (MCP).
MongoDB Lens: Full Featured MCP Server for MongoDB Database Analysis
All-in-one MCP server with AI search, RAG, and multi-service integrations (GitLab/Jira/Confluence/YouTube) for AI-enhanced development workflows
A Model Context Protocol (MCP) server that enables secure interaction with MySQL databases
A Model Context Protocol (MCP) server that provides access to NS (Dutch Railways) travel information through Claude AI. This server enables Claude to fetch real-time train travel information and disruptions using the official Dutch NS API.
This is a TypeScript-based MCP server that allows searching for New York Times articles from the last 30 days based on a keyword. It demonstrates core MCP concepts by providing: Tools for searching articles Integration with the New York Times API
MCP server for interacting with Neon Management API and databases
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.