Model Context Protocol
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Airtable Model Context Protocol Server, for allowing AI systems to interact with your Airtable bases
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.
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.
MCP Server implementation for Xcode integration. This server acts as a bridge between Claude and your local Xcode development environment, enabling intelligent code assistance, project management, and automated development tasks.
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An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
MCP Server for AI Summarization
A TypeScript implementation of a Model Context Protocol (MCP) server that integrates with PiAPI's API. PiAPI makes user able to generate media content with Midjourney/Flux/Kling/LumaLabs/Udio/Chrip/Trellis directly from Claude or any other MCP-compatible apps.
AI app store powered by 24/7 desktop history. open source | 100% local | dev friendly | 24/7 screen, mic recording
Java SDK for the Model Context Protocol (MCP), providing seamless integration between Java and Spring applications and MCP-compliant AI models and tools.
A Model Context Protocol (MCP) server that provides agentic tools for interacting with the Trieve API. This server enables AI agents to search and interact with Trieve datasets through a standardized interface.
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.