Model Context Protocol
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A Model Context Protocol (MCP) server that enables AI models to interact with Bitcoin, allowing them to generate keys, validate addresses, decode transactions, query the blockchain, and more.
A TypeScript-based MCP server that provides tools to interact with Confluence. It demonstrates core MCP concepts.
This MCP server attempts to exercise all the features of the MCP protocol. It is not intended to be a useful server, but rather a test server for builders of MCP clients. It implements prompts, tools, resources, sampling, and more to showcase MCP capabilities.
Foxy contexts is a Golang library for building context servers supporting Model Context Protocol.
This plugin provides integration between Genkit and the Model Context Protocol (MCP). MCP is an open standard allowing developers to build "servers" which provide tools, resources, and prompts to clients. Genkit MCP allows Genkit developers to both consume MCP tools, prompts, and resources as a client and provide tools and prompts as a server.
A TypeScript framework for building MCP (Model Context Protocol) servers elegantly
Enables cloud-based AI services to access local Stdio based MCP servers.
simple web ui to manage mcp (model context protocol) servers in the claude app
A Model Context Protocol (MCP) server that lets you seamlessly use OpenAI's models right from Claude.
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.