"A tool or assistant to review and suggest changes for GitHub pull requests" matching MCP servers:

Enables automated GitHub Pull Request reviews using local Ollama, Cursor CLI, or Gemini CLI as AI providers. Supports customizable review prompts, comprehensive PR analysis, and optional auto-posting of reviews to GitHub.

MCP server for interacting with GitHub pull requests and issues via natural language. Provides tools to list PRs, inspect diffs, check CI status, and post review comments with write-safety guards.

Provides GitHub PR review capabilities to LLMs, enabling automated PR analysis, review submission, and inline commenting via MCP.

An MCP server that automates code review by providing syntax checking, code explanation, and improvement suggestions using a multi-agent system.

Enables AI to perform peer review of its own code changes by displaying annotated diffs with inline comments in a VS Code/Cursor panel. The AI can analyze its modifications and provide explanations directly alongside the changed code, similar to human code review workflows.

Comprehensive MCP server for analyzing GitHub pull requests, detecting security vulnerabilities, assessing code quality, and providing risk ratings across multiple languages.

A local MCP server that reads GitHub pull request diffs and coding standards, then posts inline review comments and full reviews to PRs via any MCP client.

Enables AI assistants to perform comprehensive GitHub pull request code reviews, including analysis of code patterns, complexity, and security issues, while managing review comments and ensuring compliance with team coding standards.

A focused Model Context Protocol server for triaging and reviewing GitHub pull requests from Claude Desktop, Cursor, and other stdio-compatible MCP clients.

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

Enables MCP-compatible LLM clients to retrieve repository metadata, list and read files, search code, and fetch README content through natural-language requests.

Enables an MCP-capable assistant to review GitLab merge requests, GitHub pull requests, and pre-push local branches against ticket requirements, domain rubrics, compiler/lint pre-passes, blast-radius analysis, and SonarQube findings, and to draft inline comments or follow-up tasks in the user's chosen language. Nothing reaches a remote host until a human approves the exact content in an interactive terminal.

MCP server exposing GitHub tools for issues, pull requests, and code browsing via the GitHub REST API. Designed for local LLM clients with flat arguments and streamable HTTP support.

An MCP server that collects Pull Request comments from private GitHub repositories, including issue comments, review comments, and review summaries.

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.

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.

Enables AI code review to query semantic LSP context such as hover and definition against a specific Git commit or candidate, with verifiable receipts for the exact code state under review.

A collaborative code and markdown review tool that bridges human reviewers and AI agents, enabling both to browse files, inspect git diffs, leave structured comments, and save a final review report from the same UI in real time.

Provides offline, line-level code review for Spring and MyBatis changes, analyzing git diffs to catch issues like @Transactional self-invocation, N+1 queries, and ${} injection without needing an API key.

A local-first, auditable code review MCP server that freezes Git changes, creates immutable ReviewBundles, provides role-isolated contexts for correctness, security, architecture, and test reviewers, validates structured findings, and generates deterministic JSON/Markdown reports.