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.
An MCP server implementation that integrates the Brave Search API, providing both web and local search capabilities.
MCP-Bridge
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A middleware to provide an openAI compatible endpoint that can call MCP tools
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 server that installs other MCP servers for you
A model context protocol server to work with JetBrains IDEs: IntelliJ, PyCharm, WebStorm, etc. Also, works with Android Studio
LangChain.js client for Model Context Protocol.
MCP server for maigret, a powerful OSINT tool that collects user account information from various public sources.
A Model Context Protocol server to connect to the MIRO Whiteboard Application. Allows Board manipulation, sticky creation, bulk operations and more. Taking a photo of stickies and asking Claude to create MIRO equivalent works really well.
A Model Context Protocol server that provides MySQL database operations. This server enables AI models to interact with MySQL databases through a standardized interface.
Model Context Protocol with Neo4j. This server provides natural language interaction with Neo4j and Aura accounts.
A connector for Claude Desktop to read and search an Obsidian vault.
MCP server that interacts with Obsidian via the Obsidian rest API community plugin
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.