"Information about Gemini code" matching MCP servers:

Analyzes codebases using Repomix and LLMs to provide structured code reviews with specific issues and recommendations, supporting multiple LLM providers including OpenAI, Anthropic, and Gemini.

AI-powered code review server that analyzes git diffs and PRs with context from project guidelines and task lists. Supports integration with Claude Code and Cursor via MCP.

Tracks the complete lineage and DNA of every line of code, enabling impact analysis, bug risk prediction, and code archaeology through deterministic analysis of git history and AST.

Enables agents to query information about gems in a Ruby project's Gemfile, including source code and metadata.

Enables AI assistants to review GitLab merge requests by fetching diffs, analyzing code changes, adding comments, and managing approvals through the GitLab API. Supports comprehensive merge request analysis and version comparison for automated code review workflows.

Enables manual review of GitLab Merge Requests and GitHub Pull Requests, loading context, generating comment previews, and preparing commit-based fixes for unresolved threads. Every write — comments, replies, and commits — requires explicit user confirmation and an approved preview before it is published.

Enables fetching and analyzing Gemini Code Assist reviews from GitHub pull requests, with smart defaults and pagination.

An advanced Model Context Protocol server that integrates GitHub repositories with Google Gemini AI to provide intelligent code assistance, analysis, and repository management operations.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

An MCP bridge that lets Codex supervise Reasonix as an implementation worker in an isolated Git worktree, ensuring safe delegation with scoped writes and sandboxed execution.

A code review tool that generates detailed HTML review documents by comparing branches or commits, with author filtering and intelligent analysis.

Exposes structured Microsoft Dynamics 365 Business Central source code (versions 23-29, 47 localizations) to AI agents via MCP, enabling fast lookups, searches, and code analysis.

A Model Context Protocol server that connects GitHub code to Claude.ai. This server utilizes the Pera1 service to extract code from GitHub repositories and provide better context to Claude.

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

Enables natural-language queries about public GitHub repositories, including issues, pull requests, repo metadata, and READMEs, via the GitHub API.

MCP server for TNL (Typed Natural Language): per-feature English contracts for AI coding agents. 6 tools — get_impacted_tnls, retrieve_tnl, trace, propose_tnl_diff, approve_tnl_diff, verify — let agents look up relevant contracts, propose contract edits, and verify implementations against them. Drop-in via npx typed-nl init for Claude Code, Codex, Gemini.

Enables Codex to delegate routine repository exploration, implementation, refactors, tests, and fixes to DeepSeek Harness in isolated Git worktrees, returning compact results and patches for review while keeping the main workspace protected.

Fetches glasz-style spec files (product.md, tech.md, test-plan.md, and INDEX.md) from GitHub repositories, enabling LLMs to answer questions about features, stories, and acceptance criteria without cloning or pasting files.

MCP server for GitHub code retrieval and reuse, using SQLite+FTS5 indexing and search history to enable search-first, requirements-refined code search from GitHub repositories.