What Happened - GitHub Released Its Model Context Protocol Server GitHub has released a new open-source Model Context Protocol (MCP) server as part of its latest GitHub Copilot update. Announced in April 2025, the release marks GitHub’s first implementation of the MCP standard developed by Anthropic. The new server is a complete rewrite in Go, preserving “100% of the old server’s functionality” while adding improvements like customizable tool descriptions, integrated code scanning, and a new get_me function for natural language queries, e.g., “show me my private repos”. By releasing its own MCP server, GitHub provides an official gateway for agents to interact with GitHub features (repos, PRs, issues, etc.). Developers can thus automate GitHub workflows and processes, extract and analyze data from repositories, and build AI-powered tools and apps that interact with GH’s ecosystem. Notably, Visual Studio Code now has native support for MCP in GitHub Copilot. Community’s Reactions - Let’s Build! With close to 14,000 GitHub stars and over 150 PRs, the new Copilot agent + MCP combo is described as a kind of “awesome sauce” for agentic workflow. Copilot is no longer limited to suggesting code; it can actually take actions and fetch information on a developer’s behalf. In day-to-day workflows, developers can now ask Copilot to perform tasks that span beyond the editor. For instance, one could prompt a simple task like: “Find any markdown files in my project missing an author footer, and create a GitHub issue to track adding those”. This evolution has developers excited, not just because Copilot feels more capable, but because they can run more productive workflows and delegate real tasks, unlike ever before. Do you enjoy being informed about the AI Native Development space (AIND)? I’m helping build the AIND community, where we cover the most relevant dev-focused news. For the busy folks, we send out a crisp one-pager every week, free and straight to your inbox. Our AIND Take - GitHub’s MCP: Context and Workflows Reach New Heights Large language models only perform well when they have access to correct context, both of which need to be timely and accurate. GitHub’s MCP server addresses this core limitation by providing a structured way to integrate directly with public and private repos. This enables AI tools to operate with a real-time development context, accessing the latest repository data, issue updates, and pull request activity as it evolves. The GitHub MCP server also introduces a workflow that makes it easier for developers to move from identifying issues to generating PRs and conducting code reviews. This is the central value piece in this release: keep chatting, and the MCP takes care of both code-gen and workflow actions. This end-to-end flow brings a higher level of automation and structure to what are traditionally manual steps in the development lifecycle. A promising trend is thus the emergence of complementary MCP servers that extend support across more parts of the development workflow. For example, GitHub MCP can handle repository tasks while Context7 serves as a dependency management layer, working together to execute broader SDLC actions. When used together, these servers enable development tools to become "workflow-aware" and collaborative in nature. This will also raise key questions on accuracy and reliability: how do we ensure the MCP server’s actions, like creating issues or modifying repos, are accurate and aligned with developer intent? In an increasingly crowded landscape of MCP server implementations, we believe GitHub’s official MCP server will stand out as one of the most well-known and practically useful. It is also a sign that incumbents are taking MCP seriously. With both OpenAI and Anthropic now able to interact with GitHub, developers are gaining the ability to bring their repository context with them across different models (and platforms). Finally, bundling this with Microsoft now open-sourcing Copilot for Visual Studio Code, developers gain further control and customization in their agile workflows. What’s exciting is that AI is no longer limited to code generation via prompts - it’s now extending across the entire software development lifecycle, including GitHub repository management. With standardized protocols like MCP playing a part in the journey where builders’ intent is translated into workflow, GitHub’s release marks an important milestone. What Happened - GitHub Released Its Model Context Protocol Server What Happened - GitHub Released Its Model Context Protocol Server GitHub has released a new open-source Model Context Protocol (MCP) server as part of its latest GitHub Copilot update. Announced in April 2025, the release marks GitHub’s first implementation of the MCP standard developed by Anthropic. The new server is a complete rewrite in Go, preserving “100% of the old server’s functionality” while adding improvements like customizable tool descriptions, integrated code scanning, and a new get_me function for natural language queries, e.g., “show me my private repos”. open-source By releasing its own MCP server, GitHub provides an official gateway for agents to interact with GitHub features (repos, PRs, issues, etc.). Developers can thus automate GitHub workflows and processes, extract and analyze data from repositories, and build AI-powered tools and apps that interact with GH’s ecosystem. Notably, Visual Studio Code now has native support for MCP in GitHub Copilot. Community’s Reactions - Let’s Build! Community’s Reactions - Let’s Build! With close to 14,000 GitHub stars and over 150 PRs, the new Copilot agent + MCP combo is described as a kind of “awesome sauce” for agentic workflow. Copilot is no longer limited to suggesting code; it can actually take actions and fetch information on a developer’s behalf. “awesome sauce” In day-to-day workflows, developers can now ask Copilot to perform tasks that span beyond the editor. For instance, one could prompt a simple task like: “Find any markdown files in my project missing an author footer, and create a GitHub issue to track adding those” . This evolution has developers excited, not just because Copilot feels more capable, but because they can run more productive workflows and delegate real tasks, unlike ever before. “Find any markdown files in my project missing an author footer, and create a GitHub issue to track adding those” Do you enjoy being informed about the AI Native Development space (AIND)? I’m helping build the AIND community, where we cover the most relevant dev-focused news. For the busy folks, we send out a crisp one-pager every week, free and straight to your inbox. AIND community, AIND community, a crisp one-pager a crisp one-pager Our AIND Take - GitHub’s MCP: Context and Workflows Reach New Heights Our AIND Take - GitHub’s MCP: Context and Workflows Reach New Heights Large language models only perform well when they have access to correct context, both of which need to be timely and accurate. GitHub’s MCP server addresses this core limitation by providing a structured way to integrate directly with public and private repos. This enables AI tools to operate with a real-time development context, accessing the latest repository data, issue updates, and pull request activity as it evolves. The GitHub MCP server also introduces a workflow that makes it easier for developers to move from identifying issues to generating PRs and conducting code reviews. This is the central value piece in this release: keep chatting, and the MCP takes care of both code-gen and workflow actions. This end-to-end flow brings a higher level of automation and structure to what are traditionally manual steps in the development lifecycle. A promising trend is thus the emergence of complementary MCP servers that extend support across more parts of the development workflow. For example, GitHub MCP can handle repository tasks while Context7 serves as a dependency management layer, working together to execute broader SDLC actions. Context7 When used together, these servers enable development tools to become "workflow-aware" and collaborative in nature. This will also raise key questions on accuracy and reliability: how do we ensure the MCP server’s actions, like creating issues or modifying repos, are accurate and aligned with developer intent? In an increasingly crowded landscape of MCP server implementations, we believe GitHub’s official MCP server will stand out as one of the most well-known and practically useful. It is also a sign that incumbents are taking MCP seriously. With both OpenAI and Anthropic now able to interact with GitHub, developers are gaining the ability to bring their repository context with them across different models (and platforms). Finally, bundling this with Microsoft now open-sourcing Copilot for Visual Studio Code , developers gain further control and customization in their agile workflows. open-sourcing Copilot for Visual Studio Code What’s exciting is that AI is no longer limited to code generation via prompts - it’s now extending across the entire software development lifecycle, including GitHub repository management. With standardized protocols like MCP playing a part in the journey where builders’ intent is translated into workflow, GitHub’s release marks an important milestone.
