server-git is an MCP server designed to empower AI models with Git repository interaction capabilities. It provides a suite of tools for programmatically reading, searching, and manipulating Git repositories, enabling AI to understand code context, automate development tasks, and analyze project history.

This server allows AI models to perform actions like checking repository status, viewing diffs, committing changes, managing branches, and inspecting file contents. By providing these tools, server-git streamlines workflows, automates code reviews, and enhances AI-driven development processes.

server-git integrates seamlessly with AI models through the MCP client-server architecture, utilizing standard input/output or HTTP/SSE for communication. Developers can easily incorporate this server into their MCP configurations, unlocking a new level of AI-powered Git interaction. It can be installed via pip or run directly using uvx, and supports configuration with Claude Desktop and Zed editors.

Git Repository State Inspection

The server-git provides tools like git_status, git_diff_unstaged, and git_diff_staged that allow AI models to inspect the current state of a Git repository. These tools enable the AI to understand what files have been modified, what changes have been staged for commit, and what remains unstaged. This is crucial for AI-driven development workflows where the AI needs to assess the impact of its actions on the codebase. For example, an AI could use git_status to check if its code changes have introduced any unexpected modifications or conflicts. It can then use git_diff_unstaged to review the exact changes before staging them. This capability allows AI models to make informed decisions about code management and version control, ensuring that changes are tracked and managed effectively. The server returns the output of these commands as text, which the AI can then parse and interpret.

Automated Code Committing

The git_commit and git_add tools enable AI models to automate the process of committing code changes to a Git repository. The git_add tool allows the AI to stage specific files for commit, while the git_commit tool allows the AI to create a new commit with a specified message. This functionality is particularly useful in scenarios where the AI is making automated code changes, such as bug fixes or feature implementations. For example, an AI could automatically add and commit changes after successfully completing a code refactoring task. The AI can also generate commit messages based on the changes it has made, providing a clear and concise description of the commit. This automation streamlines the development process and reduces the manual effort required to manage code changes. The server returns a confirmation message including the new commit hash upon successful commit.

Branch Management

The server-git includes tools for managing Git branches, such as git_create_branch and git_checkout. These tools allow AI models to create new branches and switch between existing branches, enabling them to work on multiple features or bug fixes in parallel. For example, an AI could create a new branch for a specific feature implementation, make the necessary code changes, and then switch back to the main branch to continue working on other tasks. This capability is essential for collaborative development environments where multiple developers (or AIs) are working on the same codebase. The AI can also use these tools to experiment with new ideas or approaches without affecting the stability of the main branch. The server confirms the branch creation or checkout operation upon success.

Technical Implementation: Secure Repository Access

The server-git is designed to provide secure access to Git repositories. The server can be configured to restrict access to specific repositories or branches, ensuring that AI models can only access the code they are authorized to modify. This is crucial for protecting sensitive code and preventing unauthorized changes. The server also supports authentication and authorization mechanisms to verify the identity of the AI model and ensure that it has the necessary permissions to perform Git operations. This security-focused design makes the server-git a reliable and trustworthy component of the MCP ecosystem. The server leverages standard Git protocols and libraries to ensure compatibility and security.