Model Context Protocol
Search by server name, description, or features
Popular Tags
MCP server for Oura API integration. It allows language models to query sleep, readiness, and resilience data from Oura API.
An MCP server that provides access to Postman. Functionality is based on the official OpenAPI specification. This project is part of the Model Context Protocol (MCP) initiative from Anthropic.
An MCP server that provides safe, read-only access to SQLite databases through Model Context Protocol (MCP). This server is built with the FastMCP framework, which enables LLMs to explore and query SQLite databases with built-in safety features and query validation.
A Model Context Protocol (MCP) server that provides access to the Strava API. It allows language models to query athlete activities data from the Strava API.
Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI or DeepSeek using MCP protocol via tool or predefined prompts. Vendor API key required
Upsonic is a reliability-focused framework designed for real-world AI agent applications. It utilizes the Model Context Protocol (MCP) to leverage diverse tools and offers features for browser and computer use integration, as well as a secure runtime environment.
MCP Server implementation for Xcode integration. This server acts as a bridge between Claude and your local Xcode development environment, enabling intelligent code assistance, project management, and automated development tasks.
A Model-Context Protocol Server for YouTube. Uses `yt-dlp` to download subtitles from YouTube and connects it to claude.ai via Model Context Protocol.
Model Context Protocol (MCP) Server for Apify's Actors
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.