"A tool for finding relevant files in a Git project based on questions" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Provides AI assistants with progressive code intelligence to explore repository structure, find symbols, and assess the impact of changes using ast-grep.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

A token-budgeted Git MCP server and CLI that provides compact status, diff, and log summaries for AI agents to conserve context.

Enables querying git commit history to analyze when and why code changes happened, providing authorship context and diffs for specific modules.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables Claude to explore and analyze remote Git repositories, providing structured file contents and token estimates.

MCP server that makes git rebase safe for agents by refusing unsafe operations, presenting conflicts as two intents, and verifying the branch's change against its base.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables AI clients to interrogate a local Git repository's history, surfacing change hotspots, per-author activity, files that change together, single-file commit history, and draft changelogs between refs. It is strictly read-only, requires no API keys, and returns structured data for the client to interpret.

A read-only MCP server that exposes Git history, diffs, refs, and file contents to AI assistants, with strict access controls and security restrictions.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

Indexes Unreal Engine project C++ source, config files, dependencies, gameplay tags, replication, asset references, and log categories into a SQLite database and exposes tools for AI assistants to query structural and config info.

Provides deep git file-level forensics tools to analyze detailed file histories, changes, and patterns within git repositories, focusing on individual file analysis rather than repository-wide operations.

A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.

Enables AI assistants to perform code reviews by providing access to staged files, git diffs, and repository file content. It allows users to evaluate changes and context within any local git repository before committing or pushing.

An open-source MCP server that automates project customization by analyzing your codebase and generating AI-ready configuration files based on industry best practices.

Hardware-accelerated codebase mapping that indexes Git repositories into Postgres/pgvector and serves code search, relationships, and static analysis results via a stdio MCP server.

Provides AI coding agents with structured Git repository context including project state, code structure, activity, and risk analysis without modifying or uploading code.

It enables users to interact with a codebase through hybrid retrieval, code graph navigation, impact analysis, and context preparation for AI coding agents.

A self-contained Claude Code plugin that profiles a project by running a fixed DAG to emit agent-facing context pages, a human/developer guide, and a queryable vectorstore.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

Enables scanning projects for dependency vulnerabilities, secrets, license conflicts, code quality, and git health, returning a 0-100 health score with actionable suggestions.

Helps AI read GitHub repository structure and important files. Want to quickly understand what a repo is about? Prompt it with "read https://github.com/adhikasp/mcp-git-ingest and determine how the code technically works".

An MCP server that gives AI assistants deep understanding of your local Git repositories, providing instant repo overviews, change summaries, blame analysis, changelogs, branch health checks, and history search.

Security scanner for MCP servers and AI-generated code. Detects leaked API keys, PII, prompt injection, and MCP misconfigs with A-F security grades.

Enables coding agents to perform semantic Python AST diffing across git boundaries, detect breaking changes, and generate concise PR triage summaries for reviewers via the Model Context Protocol.

A local-first MCP server that provides read-only access to Git repository history, exposing commit metadata and optionally content patches via configurable policies, with optional AI-powered analysis while never modifying Git state.

Enables AI agents to run automated daily code reviews, retrieve Markdown reports, and curate a project knowledge base across any Git repository.