Model Context Protocol
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Model Context Protocol (MCP) server for Atlassian products (Confluence and Jira). This integration supports both Atlassian Cloud and Jira Server/Data Center deployments.
MCP-Bridge
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A middleware to provide an openAI compatible endpoint that can call MCP tools
An MCP server implementation that integrates the Brave Search API, providing both web and local search capabilities.
mcp-golang
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Write Model Context Protocol servers in few lines of go code. Docs at https://mcpgolang.com
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An MCP stdio to HTTP SSE transport gateway with example server and MCP client
This MCP Server is used to summarize your chat messages.
Model Context Protocol server to run commands
MCP Server is a versatile tool designed for interactive data exploration. Your personal Data Scientist assistant, turning complex datasets into clear, actionable insights.
A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools.
A Model Context Protocol server for Git repository interaction and automation. This server provides tools to read, search, and manipulate Git repositories via Large Language Models.
A Model Context Protocol Server for Home Assistant
IP Geolocation Server for MCP
MCP Server for kubernetes management commands
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.