Git Prompts MCP Server

Git Prompts MCP Server – Overview

The Git Prompts MCP Server addresses a common pain point for developers working with AI assistants: contextual awareness of code changes. When an assistant is asked to draft commit messages, pull‑request descriptions, or review diffs, it needs a reliable source of the repository’s current state and history. This server supplies that data by exposing Git‑centric commands over the Model Context Protocol, allowing tools like Claude to query a local repository and receive structured, up‑to‑date information without manual parsing or shell scripting.

At its core, the server offers a small but powerful set of commands that mirror everyday Git operations. The and commands produce diffs between the working tree, staged files, and any specified ancestor commit or branch. synthesizes a pull‑request description from those diffs and the commit history, while retrieves all messages between two points in the repository. These commands are exposed as both MCP actions and as reusable tools (, , ) that clients can invoke directly. The server also supports a flexible exclude mechanism, letting developers filter out noise such as lock files or generated artifacts.

For AI workflows, this means a seamless integration path: an assistant can ask the server for the latest diff, then feed that into a language model prompt to generate concise PR titles or detailed change logs. Because the server returns data in JSON by default, downstream systems can parse and display diffs in UI panels or feed them into CI pipelines. The ability to specify an ancestor branch or commit also allows for “diff‑between‑branches” scenarios, useful in large monorepos where feature branches diverge frequently.

Real‑world use cases include:

• Automated PR creation – A CI job could trigger the server to fetch diffs and generate a draft PR description that a developer reviews before merging.
• Code review assistance – During a live chat with an assistant, a developer can request a quick summary of changes or commit history to provide context for the model’s suggestions.
• Documentation generation – The server can supply diffs that highlight API changes, enabling an assistant to update changelogs or versioned docs automatically.

Unique advantages of this MCP server are its tight coupling to the Zed editor’s configuration system, which means it can be launched with a single JSON entry and automatically receives the repository path. It also honors user‑defined exclude patterns via command‑line arguments, ensuring that irrelevant files never pollute the diff output. By delivering structured Git data directly to AI clients, the server eliminates a layer of friction that would otherwise require custom shell scripts or third‑party APIs. This makes it an indispensable tool for developers who want their AI assistants to understand exactly what has changed in their codebase, right at the moment they need it.