Model Context Protocol
🔥 Top Viewed This Week
by Tag: Tool
Search by server name, description, or features
Popular Tags
All-in-one MCP server with AI search, RAG, and multi-service integrations (GitLab/Jira/Confluence/YouTube) for AI-enhanced development workflows
MCP Server for the Notion API, enabling Claude to interact with Notion workspaces.
MCP server for Oura API integration. It allows language models to query sleep, readiness, and resilience data from Oura API.
MCP Server for the Perplexity API.
A Model Context Protocol (MCP) server implementation for interacting with Phabricator API. This server allows LLMs to interact with Phabricator through a standardized interface.
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.
GitLab Community Edition
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.