"A service for finding coding review resources and best practices" matching MCP servers:

Gives any MCP-compatible AI chat or agent a safe, model-neutral coding runtime with file read/search, structured multi-file patches, command execution, interactive sessions, and git operations, all confined to a single workspace and gated by permission modes.

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.

A production-oriented MCP server for coding agents that enables multi-project management through secure file operations, Git integration, and safe command execution. It supports project discovery across multiple root directories and provides robust audit logging with both STDIO and HTTP transport options.

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.

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.

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

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

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

AI-powered code review using Zhipu GLM. It gathers git diffs and source context to provide focused code reviews.

Enables code review operations on GitHub and GitLab, including fetching pull/merge requests, viewing diffs, adding comments, analyzing code quality, and creating merge requests directly from your MCP client.

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 agents to securely create and manage GitHub-to-Slack review routing setups through Tenpace, using OIDC-verified browser authorization and short-lived links.

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

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 interaction with GitLab projects, merge requests, issues, and code reviews through Claude AI, providing tools for code review and project management.

Gives MCP-compatible AI clients safe, hands-on access to local codebases: file reading/search, multi-file patches, command execution, interactive sessions, Git inspection, and coordination of local agent providers such as Antigravity and OpenCode.

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

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.