Model Context Protocol
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A Model Context Protocol (MCP) server that provides web search functionality using Perplexity AI's API. Works with the Anthropic Claude desktop client.
An MCP server that provides access to Postman. Functionality is based on the official OpenAPI specification. This project is part of the Model Context Protocol (MCP) initiative from Anthropic.
A framework for building Model Context Protocol (MCP) servers elegantly in TypeScript.
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An MCP server that provides access to Postman. Functionality is based on the official OpenAPI specification. This project is part of the Model Context Protocol (MCP) initiative from Anthropic.
Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI or DeepSeek using MCP protocol via tool or predefined prompts. Vendor API key required
Enable any LLM (e.g. Claude) to interactively debug any language for you via MCP and a VS Code Extension
The fast, Pythonic way to build Model Context Protocol servers 🚀
A Model Context Protocol server for converting almost anything to Markdown
A framework for building Model Context Protocol (MCP) servers elegantly in TypeScript.
MCP server that gives Claude ability to use OpenAI's GPTs assistants
A Model Context Protocol (MCP) server that provides web search functionality using Perplexity AI's API. Works with the Anthropic Claude desktop client.
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.