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
19
A middleware to provide an openAI compatible endpoint that can call MCP tools
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A Google Tasks Model Context Protocol Server for Claude
A Model Context Protocol (MCP) server that provides tools for fetching information from Hacker News.
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
A TypeScript framework for building MCP (Model Context Protocol) servers elegantly
A MCP (model context protocol) server that gives the LLM access to and knowledge about relational databases like SQLite, Postgresql, MySQL & MariaDB, Oracle, and MS-SQL.
Enables cloud-based AI services to access local Stdio based MCP servers.
MCP server connecting to Kubernetes
simple web ui to manage mcp (model context protocol) servers in the claude app
A Model Context Protocol server that provides access to MongoDB databases. This server enables LLMs to inspect collection schemas and execute MongoDB operations.
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.