https://github.com/github/github-mcp-server

GitHub launched their official MCP server.

https://www.youtube.com/watch?v=d3QpQO6Paeg

https://modelcontextprotocol.io/

The Model Context Protocol (MCP) was introduced by Anthropic on November 24, 2024, as an open standard for connecting AI systems to data sources. The first connectors released were for GitHub, Google Drive, and Slack.

By February 2025, the developer community had created over 1000 open MCP connectors, demonstrating significant ecosystem growth and interest in the protocol. Support for MCP also gradually appeared in all major AI programming applications/extensions, including Cline/Roo, Cursor, Windsurf, and Continue.

Through MCP, you can work with Postgres, Upstash, and Slack directly in the code editor. Browsertools MCP provides access to the browser console for debugging. And https://context7.com/ provides up-to-date documentation for AI code editors.

A significant step was OpenAI's announcement on March 26, 2025, of support for MCP. Soon after, at Google Next 2025, Google announced MCP support in the SDK for their Gemini models (though they also introduced the A2A protocol). Thus, the protocol is gradually becoming universal.

Organization and Ecosystem. Following the initial repository (https://github.com/modelcontextprotocol/servers), third-party online catalogs began to emerge (such as https://opentools.com/ https://mcp.so/ https://mcpserverdirectory.org/, etc.), where you can find the necessary server. Projects for MCP managers are appearing that simplify installation, for example https://mcp-get.com/ https://mcpm.sh/ https://mcpmanager.app/ https://mcpmcp.io/, etc.

There are projects that help convert a standard REST API to MCP - for example https://rapid-mcp.com/ https://api200.co/mcp.

The problem with open catalogs is the unclear reliability of the hosted servers.

Security. Since an MCP server acts as an intermediary between the model and the data source, a malicious actor who sets up a server can log everything, including API access keys to the data. Authentication and authorization are not yet standardized within MCP.

Servers are divided into official and community types. Obviously, official servers are not intermediaries, and requests to them are analogous to requests to API endpoints. Community servers, set up by third parties, should be treated with caution, and it's worth checking who is behind them. You can also set up your own server in cloud (for example, weather on AWS lambda) or with a container via mcp-containers.

The more the protocol spreads, the more official servers will appear, as was the case with REST API.

#mcp #githubcopilot