Model Context Protocol
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Node.js server implementing Model Context Protocol (MCP) for filesystem operations.
This MCP server integrates with Google Drive to allow listing, reading, and searching over files.
A Model Context Protocol server that provides MySQL database operations. This server enables AI models to interact with MySQL databases through a standardized interface.
Airtable Model Context Protocol Server, for allowing AI systems to interact with your Airtable bases
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A Model Context Protocol (MCP) server that provides line-oriented text file editing capabilities through a standardized API. Optimized for LLM tools with efficient partial file access to minimize token usage.
A Model Context Protocol server for Zotero integration that allows Claude to interact with your Zotero library.
A middleware to provide an openAI compatible endpoint that can call MCP tools
MCP server for browser automation using Playwright. Enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a real browser environment.
MCP server for connecting agentic systems to search systems via searXNG
A simple MCP server that exposes datetime information to agentic systems and chat REPLs
Connect your chat repl to wolfram alpha computational intelligence
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.