Model Context Protocol
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MCP-Bridge
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A middleware to provide an openAI compatible endpoint that can call MCP tools
mcp-golang
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Write Model Context Protocol servers in few lines of go code. Docs at https://mcpgolang.com
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Simple solution to give Claude ability to check current time via MCP
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
A CLI host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP).
A Model Context Protocol server that enables Make scenarios to be utilized as tools by AI assistants. This integration allows AI systems to trigger and interact with your Make automation workflows.
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.
MongoDB Lens: Full Featured MCP Server for MongoDB Database Analysis
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.