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<title>MCP Ecosystem - Model Context Protocol</title> |
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<meta name="description" content="Explore the growing ecosystem of MCP implementations, tools, and community resources for the Model Context Protocol."> |
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<a href="index.html" class="logo">MCP<span>Hub</span></a> |
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<li><a href="index.html">Home</a></li> |
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<li><a href="about.html">About</a></li> |
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<li><a href="architecture.html">Architecture</a></li> |
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<li><a href="benefits.html">Benefits</a></li> |
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<li><a href="ecosystem.html">Ecosystem</a></li> |
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<li><a href="getting-started.html">Get Started</a></li> |
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</header> |
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<section class="hero"> |
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<h1>MCP Ecosystem</h1> |
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<p>Exploring the growing community of tools, implementations, and resources</p> |
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<h2>The Growing MCP Community</h2> |
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<p> |
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Since its introduction by Anthropic in 2024, the Model Context Protocol (MCP) has seen rapid adoption across the AI ecosystem. Organizations and individual developers are creating MCP servers, tools, and integrations that expand the capabilities of AI applications. |
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This page provides an overview of the MCP ecosystem, including official implementations, community contributions, and resources for developers looking to build with MCP. |
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<h2>Official SDKs and Libraries</h2> |
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Anthropic and the MCP community maintain official Software Development Kits (SDKs) for implementing MCP clients and servers in various programming languages: |
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<h3>TypeScript/JavaScript SDK</h3> |
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The TypeScript SDK provides comprehensive support for creating MCP clients and servers in JavaScript environments, including Node.js and browser applications. |
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<a href="https://github.com/modelcontextprotocol/typescript-sdk" target="_blank">GitHub Repository</a> |
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<h3>Python SDK</h3> |
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The Python SDK enables developers to build MCP clients and servers with Python, making it easy to integrate with existing Python-based AI systems and data processing pipelines. |
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<a href="https://github.com/modelcontextprotocol/python-sdk" target="_blank">GitHub Repository</a> |
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<h3>Java SDK</h3> |
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The Java SDK, maintained in collaboration with Spring AI, provides Java developers with the tools to build MCP clients and servers in Java-based environments. |
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<a href="https://github.com/modelcontextprotocol/java-sdk" target="_blank">GitHub Repository</a> |
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<div class="card"> |
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<h3>C# SDK</h3> |
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The C# SDK brings MCP support to .NET environments, allowing developers to build MCP clients and servers in C# applications. |
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<a href="https://github.com/modelcontextprotocol/csharp-sdk" target="_blank">GitHub Repository</a> |
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<h2>Reference MCP Servers</h2> |
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Anthropic and the MCP community have developed reference implementations of MCP servers for various data sources and tools: |
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<h3>Filesystem Server</h3> |
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The Filesystem MCP server provides AI models with access to the local file system, allowing them to read, write, and manipulate files. |
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<a href="https://github.com/modelcontextprotocol/server-filesystem" target="_blank">GitHub Repository</a> |
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<h3>Git Server</h3> |
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The Git MCP server enables AI models to interact with Git repositories, providing functionality for version control operations. |
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<a href="https://github.com/modelcontextprotocol/server-git" target="_blank">GitHub Repository</a> |
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<h3>Postgres Server</h3> |
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The Postgres MCP server allows AI models to query and manipulate data in PostgreSQL databases, enabling data-driven AI applications. |
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<a href="https://github.com/modelcontextprotocol/server-postgres" target="_blank">GitHub Repository</a> |
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<h3>Google Drive Server</h3> |
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The Google Drive MCP server provides AI models with access to files and documents stored in Google Drive, enabling collaboration and document processing. |
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<a href="https://github.com/modelcontextprotocol/server-google-drive" target="_blank">GitHub Repository</a> |
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<div class="card-container" style="margin-top: 2rem;"> |
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<h3>Slack Server</h3> |
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The Slack MCP server enables AI models to interact with Slack workspaces, accessing channels, messages, and other Slack functionality. |
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</p> |
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<a href="https://github.com/modelcontextprotocol/server-slack" target="_blank">GitHub Repository</a> |
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<h3>GitHub Server</h3> |
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The GitHub MCP server allows AI models to interact with GitHub repositories, issues, pull requests, and other GitHub features. |
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<a href="https://github.com/modelcontextprotocol/server-github" target="_blank">GitHub Repository</a> |
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<h3>Puppeteer Server</h3> |
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The Puppeteer MCP server enables AI models to control a headless Chrome browser, allowing for web scraping, testing, and automation. |
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<a href="https://github.com/modelcontextprotocol/server-puppeteer" target="_blank">GitHub Repository</a> |
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<h3>Browser Extension Server</h3> |
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The Browser Extension MCP server allows AI models to interact with web browsers through browser extensions, enabling web-based AI applications. |
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<a href="https://github.com/modelcontextprotocol/server-browser-extension" target="_blank">GitHub Repository</a> |
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<h2>Community Contributions</h2> |
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The MCP community has created numerous additional servers, tools, and integrations that extend the capabilities of the MCP ecosystem: |
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<h3>MCP Agent</h3> |
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MCP Agent is a framework for building effective agents using Model Context Protocol and simple workflow patterns, created by LastMile AI. |
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<a href="https://github.com/lastmile-ai/mcp-agent" target="_blank">GitHub Repository</a> |
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<h3>Docker MCP Servers</h3> |
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Docker has worked with Anthropic to create Docker images for MCP servers, simplifying deployment and distribution of MCP implementations. |
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<a href="https://hub.docker.com/r/mcp" target="_blank">Docker Hub</a> |
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<h3>OpenAI Agents SDK</h3> |
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The OpenAI Agents SDK includes support for MCP, enabling OpenAI models to connect with MCP servers for enhanced capabilities. |
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<a href="https://github.com/openai/openai-agents-python" target="_blank">GitHub Repository</a> |
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<h3>MCP Server Templates</h3> |
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Community-maintained templates for creating new MCP servers, providing starting points for developers building custom MCP implementations. |
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<a href="https://github.com/modelcontextprotocol/server-templates" target="_blank">GitHub Repository</a> |
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</p> |
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</div> |
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</section> |
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<h2>MCP-Compatible AI Clients</h2> |
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Several AI applications and platforms have integrated MCP support, allowing them to connect with MCP servers: |
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<h3>Claude Desktop</h3> |
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Claude Desktop is Anthropic's desktop application for interacting with Claude AI models. It includes built-in support for connecting to MCP servers, allowing Claude to access local files, databases, and other resources. |
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<a href="https://www.anthropic.com/claude-desktop" target="_blank">Learn More</a> |
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<div> |
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<h3>Development Environments</h3> |
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Several development environments and code editors have integrated MCP support, including: |
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<ul style="margin-left: 2rem; margin-bottom: 1.5rem;"> |
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<li>Zed - A high-performance, multiplayer code editor</li> |
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<li>Replit - An online IDE with AI coding assistance</li> |
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<li>Codeium - An AI code completion and assistant tool</li> |
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<li>Sourcegraph - A code search and intelligence platform</li> |
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</ul> |
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</section> |
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<h2>Documentation and Resources</h2> |
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<h3>Official Documentation</h3> |
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The official MCP documentation provides comprehensive guides, references, and tutorials for working with the Model Context Protocol. |
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<a href="https://modelcontextprotocol.io" target="_blank">Visit Documentation</a> |
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</p> |
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<h3>Specification</h3> |
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The MCP specification defines the protocol in detail, including message formats, communication patterns, and security considerations. |
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<a href="https://modelcontextprotocol.io/specification" target="_blank">View Specification</a> |
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<h3>Community Forums</h3> |
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The MCP community forums provide a place for developers to ask questions, share ideas, and collaborate on MCP projects. |
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</p> |
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<p> |
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<a href="https://github.com/modelcontextprotocol/discussions" target="_blank">Join Discussions</a> |
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</p> |
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</div> |
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<div class="card"> |
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<h3>Examples and Tutorials</h3> |
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The MCP examples repository provides sample code and tutorials for building MCP clients and servers in various programming languages. |
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</p> |
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<a href="https://github.com/modelcontextprotocol/examples" target="_blank">Explore Examples</a> |
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</section> |
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<h2>Early Adopters and Case Studies</h2> |
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<h3>Block (Square)</h3> |
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Block (formerly Square) was an early adopter of MCP, integrating it into their systems to enhance AI capabilities across their platform. They've reported significant improvements in development efficiency and AI functionality. |
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<a href="https://block.xyz/stories/ai-integration-with-mcp" target="_blank">Read Case Study</a> |
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</div> |
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<div> |
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<h3>Apollo GraphQL</h3> |
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<p> |
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Apollo has integrated MCP into their GraphQL platform, enabling AI systems to interact with GraphQL APIs through a standardized interface. This has enhanced the capabilities of AI-powered features in their products. |
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<a href="https://www.apollographql.com/blog/apollo-and-mcp" target="_blank">Read Case Study</a> |
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</p> |
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<div class="two-column" style="margin-top: 2rem;"> |
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<div> |
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<h3>Zed Editor</h3> |
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<p> |
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Zed, a high-performance code editor, has integrated MCP to enable its AI assistants to access files, Git repositories, and other developer tools. This integration enhances the AI's ability to assist with coding tasks. |
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</p> |
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<p> |
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<a href="https://zed.dev/blog/mcp-integration" target="_blank">Read Case Study</a> |
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</div> |
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<div> |
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<h3>Replit</h3> |
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Replit, an online IDE and coding platform, has adopted MCP to enhance its AI coding assistance features, allowing its AI tools to better understand and interact with users' code. |
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</p> |
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<p> |
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<a href="https://replit.com/blog/mcp-ai-coding" target="_blank">Read Case Study</a> |
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</p> |
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</div> |
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</div> |
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</section> |
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<section> |
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<h2>Contributing to the MCP Ecosystem</h2> |
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The MCP ecosystem is open to contributions from developers and organizations. Here are some ways to get involved: |
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</p> |
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<h3>Develop MCP Servers</h3> |
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<p> |
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Create new MCP servers for data sources or tools that aren't yet supported. The MCP community welcomes servers for databases, APIs, file formats, and more. |
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</p> |
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<a href="https://github.com/modelcontextprotocol/community-servers" target="_blank">Community Servers</a> |
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</p> |
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</div> |
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<div class="card"> |
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<h3>Improve SDKs</h3> |
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<p> |
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Contribute to the official MCP SDKs by adding features, fixing bugs, or improving documentation. The SDKs are open source and welcome contributions. |
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</p> |
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<p> |
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<a href="https://github.com/modelcontextprotocol" target="_blank">MCP GitHub Organization</a> |
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</p> |
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</div> |
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<div class="card"> |
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<h3>Share Examples</h3> |
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<p> |
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Create and share examples of MCP usage to help others learn and understand the protocol. Examples can include tutorials, sample code, or case studies. |
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</p> |
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<a href="https://github.com/modelcontextprotocol/examples" target="_blank">Examples Repository</a> |
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<h3>Join Discussions</h3> |
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Participate in community discussions to share ideas, ask questions, and collaborate with other MCP developers. The MCP community is active and welcoming. |
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</p> |
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<p> |
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<a href="https://github.com/modelcontextprotocol/discussions" target="_blank">Join Discussions</a> |
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</p> |
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</div> |
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</div> |
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</section> |
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<section> |
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<h2>Future Directions</h2> |
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The MCP ecosystem continues to evolve, with several exciting developments on the horizon: |
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<ul style="margin-left: 2rem; margin-bottom: 1.5rem;"> |
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<li> |
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<strong>Remote MCP Servers:</strong> Support for remote MCP servers with enterprise-grade authentication, enabling broader deployment options. |
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<strong>Enhanced Security Features:</strong> Additional security features to protect sensitive data and ensure secure communication between clients and servers. |
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<li> |
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<strong>Broader Language Support:</strong> SDKs for additional programming languages to make MCP accessible to more developers. |
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<strong>Integration with AI Platforms:</strong> Deeper integration with AI platforms and frameworks to streamline the use of MCP in AI applications. |
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</li> |
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<li> |
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<strong>Community-Driven Standards:</strong> Evolution of the MCP specification based on community feedback and real-world usage. |
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</li> |
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</ul> |
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<p> |
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The growth and development of the MCP ecosystem will be driven by community contributions and the needs of AI developers and users. |
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</p> |
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</section> |
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</main> |
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<footer> |
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<div class="container footer-container"> |
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<div> |
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<h4>MCP Resources</h4> |
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<ul> |
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<li><a href="https://modelcontextprotocol.io" target="_blank">Official Documentation</a></li> |
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<li><a href="https://github.com/modelcontextprotocol" target="_blank">GitHub Repository</a></li> |
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<li><a href="https://www.anthropic.com/news/model-context-protocol" target="_blank">Anthropic MCP Announcement</a></li> |
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</ul> |
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</div> |
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<div> |
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<h4>Learn More</h4> |
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<ul> |
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<li><a href="about.html">About MCP</a></li> |
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<li><a href="architecture.html">Architecture</a></li> |
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<li><a href="benefits.html">Benefits</a></li> |
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<li><a href="ecosystem.html">Ecosystem</a></li> |
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</ul> |
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</div> |
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<div> |
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<h4>Community</h4> |
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<ul> |
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<li><a href="https://github.com/modelcontextprotocol/discussions" target="_blank">Discussions</a></li> |
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<li><a href="https://github.com/modelcontextprotocol/community-servers" target="_blank">Community Servers</a></li> |
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</ul> |
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</div> |
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</div> |
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<div class="copyright container"> |
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<p>© 2025 MCP Information Hub. Model Context Protocol is an open source project developed by Anthropic, PBC.</p> |
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<script src="js/main.js"></script> |
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