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

Enables AI agents to submit code snippets for review and receive structured quality reports covering correctness, security, performance, maintainability, and best practices.

Enables Claude to perform thorough code reviews by integrating with Codex and Gemini CLIs to provide senior-level feedback on code quality, security, performance, and best practices. Supports reviewing code snippets, individual files, or entire directories with automatic detection of available review tools.

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

Enables AI coding agents to receive continuous, structured software-quality feedback from Jev across multiple quality dimensions while working locally.

Enables local candidate review of ONNX or TFLite models by checking static evidence and externally measured results against a fixed policy, producing accept/reject/hold evidence ZIPs for AI agent workflows.

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.

Provides safe repository operations, skill reading, command execution, and test detection for coding agents over stdio.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.

An MCP server that enables code review by having two LLMs (Claude and GPT-4o) independently evaluate code and then synthesize their findings into a unified report.

Enables Claude to interact with R package development workflows, including CRAN metadata lookup, dependency checking, testing, documentation validation, and release automation.

AI-powered code review tool that detects AI-generated code defects invisible to traditional linters — hallucinated packages, deprecated APIs, cross-file contradictions, hidden security anti-patterns, and over-engineering. Works as a standalone CLI, GitHub Action, or MCP server. Supports TypeScript, Python, Java, Go, and Kotlin. Free for individuals, no API key required.

Enables deterministic IELTS answer checking, evidence-grounded explanations, error-cause classification, spaced repetition of mistakes, and progress reports, with data stored locally.

An MCP server that visually reviews UI edit requests by comparing screenshots before and after edits, ensuring changes satisfy user requests.

It enables AI agents and CI to run profile-driven SOAP/REST service tests with automatic login/session handling, test-customer locking, masked transaction-log/HAR catalog import, and cross-environment scenario execution.

Enables Codex CLI to perform code reviews on uncommitted changes via an MCP tool, keeping review context separate from the main session.

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.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables visual review of frontend UI variants by providing an MCP tool that opens, refreshes, verifies, captures, and closes review surfaces.

Lets an AI coding agent journal its edits, commands, checkpoints, intents and test evidence locally, then compile them into a machine-readable Change Package plus a human-readable review summary with statically computed risks. Optionally publishes the result as a GitHub Draft PR with inline comments on the exact diff lines, always gated behind explicit confirmation and redaction.

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.

Lets Claude Code read in-browser review comments, element removals, and text/CSS edits made on localhost dev pages, complete with selectors, HTML, React component names, source files, and screenshots. It also lets the agent claim tasks as in progress and submit solutions for the user to accept or reopen.

MCP server for automated code review using AI agents. It analyzes code diffs or file paths for bugs, security issues, and style violations.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.

Analyzes React component changes by performing structural analysis and generating visual diffs to identify pixel-level differences. It integrates with Figma to validate implementation compliance against design specifications and automates component reviews across git branches.

MCP coding agent with read-only tools and one paid tool for Paybond sandbox integration, enabling quick smoke testing and agent operations.

MCP server for Jama Connect that brings requirements, traceability, tests, and baselines into MCP clients like Claude, Cursor, VS Code, or GitHub Copilot, with access control, audit trail, and rate limiting. It provides 53 tools across 8 individually enableable toolsets, with an admin dashboard for managing access and usage.

Autonomous code quality review and verification framework enforcing ISO/IEC 25010 and OWASP ASVS standards for AI-assisted engineering.

Local MCP server for Cursor that analyzes code, finds bugs, generates tests and documentation via OpenRouter.

Reviews every PR for security, bugs, and performance, then fixes the findings through MCP, keeping you in control of what merges.

Enables automated WCAG 2.2 AA accessibility audits of Figma designs and webpages. Generates detailed markdown reports with severity-grouped violations, specific criterion references, and concrete fix recommendations.