Model Context Protocol
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Shell and coding agent on claude desktop app.
This Model Context Protocol server implementation of Asana allows you to talk to Asana API from MCP Client such as Anthropic's Claude Desktop Application, and many more.
Simple solution to give Claude ability to check current time via MCP
A middleware to provide an openAI compatible endpoint that can call MCP tools
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).
A Model Context Protocol (MCP) server for launching and managing macOS applications.
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 C# SDK implementation of 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.