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

Provides a privacy-first adaptive review engine with local SQLite storage, enabling item creation, due review retrieval, grading, and statistics via MCP tools.

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.

An MCP server that connects Claude to your real GitHub activity and tells you what to build and ship publicly to make your resume credible.

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.

Enables automated GitHub pull request review through a multi-agent system using LangGraph and MCP tools, analyzing PR metadata, files, patches, comments, and policies with RAG, guardrails, HITL approval, and Langfuse observability.

Lets MCP-compatible clients answer natural-language questions about your GitHub activity, such as counting today's commits across all your repositories via the GitHub REST API.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

Enables querying a personal GitHub repository of solved LeetCode problems via natural language, including topic-based search and live retrieval of solution code with difficulty and tags.

Local MCP server for safe GitHub developer workflows. Enables pulling main, creating feature branches, pushing them, and opening ready-for-review pull requests via tools like github_create_feature_branch and github_create_pull_request.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

A read-only MCP server that lets AI assistants inspect local workspace files, search context, view git diffs, and fetch a fixed GitHub profile, all within a sandboxed stdio transport.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Helps support engineers find similar GitHub issues to speed up troubleshooting by searching repositories and calculating similarity scores based on issue descriptions.

A custom MCP tool that integrates Perplexity AI's API with Claude Desktop, allowing Claude to perform web-based research and provide answers with citations.

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.

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.

An MCP server that tracks the historical changes of Twitter usernames—frequent screen name changes in crypto projects can be a red flag for potential scam risks.

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.

Captures a coding agent's session into an Intent Document, enabling guided and verifiable pull-request reviews on GitHub.