Model Context Protocol
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An MCP server that installs other MCP servers for you
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
docker-mcp
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A docker MCP Server (modelcontextprotocol) for seamless container and compose stack management through Claude AI.
A Model Context Protocol (MCP) server that provides tools for fetching dependency information from Clojars, the Clojure community's artifact repository.
A Model Context Protocol server for Excel file manipulation. This server enables workbook creation, data manipulation, formatting, and advanced Excel features.
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A Model Context Protocol (MCP) server that provides tools for fetching dependency information from Clojars, the Clojure community's artifact repository.
Node.js server implementing Model Context Protocol (MCP) for filesystem operations.
A Google Tasks Model Context Protocol Server for Claude
MCP server connecting to Kubernetes
A Model Context Protocol (MCP) server that lets you seamlessly use OpenAI's models right from Claude.
Shell and coding agent on claude desktop app.
A Model Context Protocol server for Zotero integration that allows Claude to interact with your Zotero library.
A simple MCP server that exposes datetime information to agentic systems and chat REPLs
A CLI host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP).
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.