"Using LLM for Automated Code Review and Validation" matching MCP servers:

Deterministic code review MCP server that provides tools for file selection, rule matching, comment positioning, and reflection, ensuring stable review quality without LLM calls.

An MCP server for automated code review of GitHub pull requests. It checks security, quality, and license issues, and provides tools to list, inspect, and review PRs.

An MCP server that integrates AI assistants like Claude with GitLab's merge requests, allowing them to review code changes, add comments, and approve/unapprove merge requests directly through the GitLab API.

Enables AI assistants to review GitHub and GitLab pull requests and merge requests, supporting multiple transports and custom review rules.

Enables comprehensive GitHub PR reviews through Cursor's AI by fetching PR diffs, running static analysis tools (ESLint, Prettier, TypeScript, Semgrep), executing tests, and generating detailed code review reports with inline comments.

Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.

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.

Open-source AI code review MCP server for local git diff auditing with deterministic security rules and AI-powered analysis using any OpenAI-compatible model.

Enables automated code review and GitHub PR commenting through MCP integration.

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

MCP Server providing AI agents with tooling for Gerrit code review workflows via stdio transport.

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.

Enables AI assistants to review GitLab merge requests by fetching changes, analyzing diffs, adding comments, and managing approvals through the GitLab API. Supports complete merge request analysis, file-specific reviews, and version comparisons.

Connects LLMs to GitHub and GitLab to analyze pull and merge requests for logic, security, and architectural alignment. It provides tools for fetching diffs, file contents, and project metadata, alongside guided prompts for professional code reviews.

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.

Enables AI assistants to interact with GitLab merge requests, review code changes, search projects, and create draft comments for 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.

Integrates GitHub repository management and local file system access to enable AI agents to perform code reviews and manage pull requests. It provides tools for listing repositories, retrieving PR diffs, and searching or reading files within a specified workspace.

Enables interactive GitHub pull-request review from Claude Code, with tools to fetch PRs, inspect files and repo structure, post review comments, and query a RAG index of the codebase.

A Model Context Protocol server that provides read-only access to GitHub repositories, enabling AI assistants to perform code reviews without write permissions.