Git Mcp

git-mcp is a Model Context Protocol server that transforms Git repositories and static sites into structured context providers for AI assistants. It functions as a documentation retrieval tool and repository indexer, exposing codebases and project files as standardized tools to reduce hallucinations in large language model responses.

The project converts raw repository files, READMEs, and external URLs into formats optimized for token consumption. It enables AI agents to perform query-based code searches and retrieve specific sections of project documentation to maintain up-to-date technical context.

The system includes capabilities for dynamic documentation indexing, remote repository fetching, and an embedded web interface for in-browser documentation chat.

Features

Documentation Search - Implements a search system that indexes technical documentation for machine-readable retrieval and natural language querying via MCP.

MCP Servers - Implements a Model Context Protocol server that exposes repository files and documentation as tools for AI models.

Model Context Protocol - Implements the Model Context Protocol to connect AI models to local data sources and external tools.

AI Coding Assistant Integrations - Provides standardized server configurations that register project context for AI coding assistants.

Codebase Context Providers - Transforms codebases and static sites into structured context to reduce hallucinations in LLM responses.

Technical Documentation Retrieval - Provides a searchable interface for querying live project documentation and source code via a standardized protocol.

Knowledge Retrieval Sources - Provides mechanisms for attaching project documentation and source code as knowledge sources for informed agent execution.

Code Repository to LLM-Ready Text Transformers - Transforms Git repositories and static sites into structured, LLM-optimized text formats.

Documentation Indexing - Parses codebase structures and READMEs to provide a baseline context map for intelligent coding assistants.

AI-Optimized Git Repository Ingestors - Converts Git repositories into structured, LLM-ready text while preserving file hierarchy and context.

Code Search Tools - Provides utilities for searching through source code repositories to extract technical implementation details for AI models.

Context-Aware Knowledge Managers - Implements hierarchical resource organization to load technical references on demand, optimizing LLM token usage.

Codebase Context Querying - Provides systems for querying codebase structure and external documentation to inform AI agent responses.

Codebase Extraction Tools - Extracts high-level project overviews and README files into text formats for LLM analysis.

Code-Specific Search Utilities - Searches through source files using targeted queries to extract implementation details and technical examples.

Remote Repository Code Fetchers - Retrieves source code and markdown files from remote version control systems via API for real-time analysis.

AI-Optimized Content Converters - Retrieves and converts content from external URLs into a format optimized for AI assistant processing.

Web Chat Interfaces - Ships an embedded browser-based chat interface for querying project documentation.

Documentation Chat Interfaces - Ships an embedded web interface that allows users to query project documentation and receive AI-generated answers in-browser.

Development & Execution - Remote access to GitHub repositories and documentation.

idosalgit-mcp

Features

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