Git AI Agent Skills

Implement GitOps workflows with ArgoCD and Flux for automated, declarative Kubernetes deployments with continuous reconciliation. Use when implementing GitOps practices, automating Kubernetes deployments, or setting up declarative infrastructure management.

Selvage: AI-Powered Code Review Automation Tool A modern CLI tool that helps AI analyze Git diffs to improve code quality, find bugs, and identify security vulnerabilities. AI Agents : Read our documentation at https://selvage.ai/llms.txt ▶ Watch Demo Video Selvage: Code reviews with an edge! No more waiting for reviews! AI instantly analyzes your code changes to provide quality improvements an

Backend: Node.js with Express.js

A Model Context Protocol (MCP) server implementation that integrates with gitingest for turning any Git repository into a simple text digest of its codebase. - Easy integration with AI assistants through the Model Context Protocol - Git repository analysis and ingestion capabilities - Support for filtering files by size, patterns, and branches - Returns comprehensive repository information includi

A Model Context Protocol (MCP) server that helps read GitHub repository structure and important files. Inspired by gitingest. Using mcp-client-cli:

Secure environment variable management with Varlock. Use when handling secrets, API keys, credentials, or any sensitive configuration. Ensures secrets are never exposed in terminals, logs, traces, or Claude's context. Trigger phrases include "environment variables", "secrets", ".env", "API key", "credentials", "sensitive", "Varlock".

Git-aware undo by logical work unit (track, phase, or task)

What is GitMCP • Features • Getting Started • How It Works • Examples • Contributing • Stop vibe-hallucinating and start vibe-coding! GitMCP is a free, open-source, remote Model Context Protocol (MCP) server that transforms any GitHub project (repositories or GitHub pages) into a documentation hub. It enables AI tools like Cursor to access up-to-date documentation and code, even if the LLM has nev

Query OpenAI models directly from Claude using MCP protocol. Add to claudedesktopconfig.json: MIT License

mcp-difyworkflow-server is an mcp server Tools application that implements the query and invocation of Dify workflows, supporting the on-demand operation of multiple custom Dify workflows. - "base-url":"http://localhost/v1" The base URL of the Dify platform api server url. - "command":"mcp-difyworkflow-server" You can specify the absolute path for the compiled binary, or create a symbolic link wit

Draft a new release. Bumps version, generates CHANGELOG.md from git history, and creates a PR.

Orchestrate a comprehensive git workflow from code review through PR creation, leveraging specialized agents for quality assurance, testing, and deployment readiness. This workflow implements modern g

You are a PR optimization expert specializing in creating high-quality pull requests that facilitate efficient code reviews. Generate comprehensive PR descriptions, automate review processes, and ensu

An MCP server for semantic code search & navigation that helps AI agents work efficiently without burning through costly tokens. Instead of reading entire files, agents can search conceptually and jump directly to the specific functions, classes, and code chunks they need. - OpenAI API Key: Required for generating embeddings (local embedding support planned) - Git: Must be a git repository (respec

Secure environment variable management ensuring secrets are never exposed in Claude sessions, terminals, logs, or git commits

English | 中文 Zero-dependency MCP memory server for AI agents — persistent, searchable, local-first, single binary. - No infra to babysit. Single Go binary. No Docker, no Node.js runtime, no cloud account, no API keys. brew install in 30 seconds. - Memory stays with the project. Stored in .aimemo/ next to your code — commit it to git or add it to .gitignore. Switch branches; memory follows the dire

if macbook or linux If the network is slow, you can set up a domestic mirror source. Method 1: On the setting page of cherry-studio, click on the MCP server, then click "Add Server", and subsequently configure it on the page. Method 2: Use the configuration parameters

This repository contains an implementation of a Model Context Protocol (MCP) server for the Royal Spanish Academy (RAE) API. It allows language models to interact with RAE's dictionary and linguistic resources. Run the server with stdio transport (for integration with LLMs): Or run it as an SSE server: The MCP server exposes the following tools to LLMs: 1. search - Search RAE API for information -

An MCP server focused only on Overleaf projects (via Overleaf Git sync). .env example: - OVERLEAFTOKEN is required. - projectid can be passed per tool call, or use default PROJECTID. - Overleaf Git access requires a plan that supports Git integration. Add to ~/.config/Claude/claudedesktopconfig.json: - Python 3.13+ - uv package manager MIT - See LICENSE

Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification

A modular and extensible Model Context Protocol (MCP) server for Jira and GitHub integration, enabling end-to-end automation of developer workflows - from issue tracking to code changes and pull request management - via AI agents inside the IDE. - Jira integration: fetch issues by filters, search via JQL, and transition issues across workflows - GitHub integration: create branches, open and merge

A Model Context Protocol (MCP) server that allows controlling macOS through SwiftAutoGUI. This server provides tools for programmatically controlling the mouse and keyboard through MCP clients. - macOS 15.0 or later - Swift 6.0 or later - Xcode 16.0 or later 1. Clone this repository: 3. Add command to your MCP client. The server provides the following tools for controlling macOS: - Tool name: move

AI pair programming in your terminal. Model-agnostic harness that speaks to Claude, GPT, Gemini, and local models. Best-in-class git integration with auto-commits per edit.

Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters).