The Growing MCP Community
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.
This page provides an overview of the MCP ecosystem, including official implementations, community contributions, and resources for developers looking to build with MCP.
Official SDKs and Libraries
Anthropic and the MCP community maintain official Software Development Kits (SDKs) for implementing MCP clients and servers in various programming languages:
TypeScript/JavaScript SDK
The TypeScript SDK provides comprehensive support for creating MCP clients and servers in JavaScript environments, including Node.js and browser applications.
Python SDK
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.
Java SDK
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.
C# SDK
The C# SDK brings MCP support to .NET environments, allowing developers to build MCP clients and servers in C# applications.
Reference MCP Servers
Anthropic and the MCP community have developed reference implementations of MCP servers for various data sources and tools:
Filesystem Server
The Filesystem MCP server provides AI models with access to the local file system, allowing them to read, write, and manipulate files.
Git Server
The Git MCP server enables AI models to interact with Git repositories, providing functionality for version control operations.
Postgres Server
The Postgres MCP server allows AI models to query and manipulate data in PostgreSQL databases, enabling data-driven AI applications.
Google Drive Server
The Google Drive MCP server provides AI models with access to files and documents stored in Google Drive, enabling collaboration and document processing.
Slack Server
The Slack MCP server enables AI models to interact with Slack workspaces, accessing channels, messages, and other Slack functionality.
GitHub Server
The GitHub MCP server allows AI models to interact with GitHub repositories, issues, pull requests, and other GitHub features.
Puppeteer Server
The Puppeteer MCP server enables AI models to control a headless Chrome browser, allowing for web scraping, testing, and automation.
Browser Extension Server
The Browser Extension MCP server allows AI models to interact with web browsers through browser extensions, enabling web-based AI applications.
Community Contributions
The MCP community has created numerous additional servers, tools, and integrations that extend the capabilities of the MCP ecosystem:
MCP Agent
MCP Agent is a framework for building effective agents using Model Context Protocol and simple workflow patterns, created by LastMile AI.
Docker MCP Servers
Docker has worked with Anthropic to create Docker images for MCP servers, simplifying deployment and distribution of MCP implementations.
OpenAI Agents SDK
The OpenAI Agents SDK includes support for MCP, enabling OpenAI models to connect with MCP servers for enhanced capabilities.
MCP Server Templates
Community-maintained templates for creating new MCP servers, providing starting points for developers building custom MCP implementations.
MCP-Compatible AI Clients
Several AI applications and platforms have integrated MCP support, allowing them to connect with MCP servers:
Claude Desktop
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.
Development Environments
Several development environments and code editors have integrated MCP support, including:
- Zed - A high-performance, multiplayer code editor
- Replit - An online IDE with AI coding assistance
- Codeium - An AI code completion and assistant tool
- Sourcegraph - A code search and intelligence platform
Documentation and Resources
Official Documentation
The official MCP documentation provides comprehensive guides, references, and tutorials for working with the Model Context Protocol.
Specification
The MCP specification defines the protocol in detail, including message formats, communication patterns, and security considerations.
Community Forums
The MCP community forums provide a place for developers to ask questions, share ideas, and collaborate on MCP projects.
Examples and Tutorials
The MCP examples repository provides sample code and tutorials for building MCP clients and servers in various programming languages.
Early Adopters and Case Studies
Block (Square)
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.
Apollo GraphQL
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.
Zed Editor
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.
Replit
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.
Contributing to the MCP Ecosystem
The MCP ecosystem is open to contributions from developers and organizations. Here are some ways to get involved:
Develop MCP Servers
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.
Improve SDKs
Contribute to the official MCP SDKs by adding features, fixing bugs, or improving documentation. The SDKs are open source and welcome contributions.
Share Examples
Create and share examples of MCP usage to help others learn and understand the protocol. Examples can include tutorials, sample code, or case studies.
Join Discussions
Participate in community discussions to share ideas, ask questions, and collaborate with other MCP developers. The MCP community is active and welcoming.
Future Directions
The MCP ecosystem continues to evolve, with several exciting developments on the horizon:
- Remote MCP Servers: Support for remote MCP servers with enterprise-grade authentication, enabling broader deployment options.
- Enhanced Security Features: Additional security features to protect sensitive data and ensure secure communication between clients and servers.
- Broader Language Support: SDKs for additional programming languages to make MCP accessible to more developers.
- Integration with AI Platforms: Deeper integration with AI platforms and frameworks to streamline the use of MCP in AI applications.
- Community-Driven Standards: Evolution of the MCP specification based on community feedback and real-world usage.
The growth and development of the MCP ecosystem will be driven by community contributions and the needs of AI developers and users.