git-commit-aider MCP Server

Git Commit Aider MCP Server

The Git Commit Aider MCP server solves a common pain point for developers working with AI‑driven code assistants: tracking and attributing the contributions that an assistant makes to a repository. When an AI modifies files, those changes normally sit in the working tree until a human commits them. Without explicit attribution, it is hard to separate AI‑generated code from human work, which can hinder auditing, collaboration, and analytics. This server automates the commit process on behalf of an AI assistant, ensuring that every change it introduces is tagged with a distinct committer identity.

At its core, the server exposes a single tool called . The tool accepts a commit message and an optional working directory, stages all changes in that directory, and runs . Crucially, it appends “(aider)” to the committer name, allowing downstream tooling to recognize the commit as AI‑generated. The tool pulls the committer’s name and email from environment variables (, ) or falls back to the local Git configuration. This design keeps credentials out of the code and respects existing user settings while guaranteeing a consistent AI marker.

Developers can integrate this server into their editor or workflow by adding it to the MCP configuration. Once active, an AI assistant can simply be prompted with a natural language request such as “Commit the changes for me,” and the server will perform the commit automatically. Because the committer name is modified, any subsequent analysis—whether via custom scripts or tools like —can isolate AI contributions by filtering on the “(aider)” tag. This facilitates accurate line‑count metrics, impact assessments, and compliance reporting.

Real‑world scenarios where Git Commit Aider shines include continuous integration pipelines that rely on AI to refactor or generate boilerplate code, collaborative projects where contributors want clear visibility into automated changes, and open‑source initiatives that track the provenance of code for licensing or security audits. By embedding commit attribution into the AI workflow, teams gain transparency without manual intervention.

Unique advantages of this MCP server are its minimal footprint—only one tool is required—and its seamless integration with existing Git workflows. It respects user‑defined identities, supports arbitrary working directories, and eliminates the need for post‑commit author rewriting. The server thus offers a lightweight, reliable solution to a nuanced problem in AI‑augmented development environments.