Model Context Protocol
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by Tag: ModelContextProtocol
MCP-Bridge
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A middleware to provide an openAI compatible endpoint that can call MCP tools
mcp-golang
13
Write Model Context Protocol servers in few lines of go code. Docs at https://mcpgolang.com
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A Model Context Protocol (MCP) server for interacting with the App Store Connect API. This server provides tools for managing apps, beta testers, bundle IDs, devices, and capabilities in App Store Connect.
A Model Context Protocol server that provides access to BigQuery. This server enables LLMs to inspect database schemas and execute queries.
A secure Model Context Protocol (MCP) server implementation for executing controlled command-line operations with comprehensive security features.
Foxy contexts is a Golang library for building context servers supporting Model Context Protocol.
Model Context Protocol (MCP) server implementation providing Google News search capabilities via SerpAPI, with automatic news categorization and multi-language support.
A TypeScript framework for building MCP (Model Context Protocol) servers elegantly
simple web ui to manage mcp (model context protocol) servers in the claude app
A Model Context Protocol server that provides access to MongoDB databases. This server enables LLMs to inspect collection schemas and execute MongoDB operations.
Model Context Protocol server for interacting with iaptic. This server allows Claude or other AIs to interact with your Iaptic data to answer questions about your customers, purchases, transactions, and statistics.
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.