code-review-mcp-server
An MCP server that provides senior-level code review, quality checks, security analysis, and refactoring suggestions directly in your editor.
README
Code Review MCP Server
Status: archived / portfolio reference. Built March 2026 as a focused exploration of FastMCP + AST-based code-quality heuristics. The deterministic tools (Ruff / ShellCheck / ESLint wrappers, secret-pattern checks) still work; the LLM-style review feedback is largely overlapped by modern coding assistants, which is why this is frozen rather than actively maintained. Fork if you want to extend.
An open-source Model Context Protocol (MCP) server that brings senior-level code review into your editor. Use it with Cursor or any MCP client to get quality checks, refactor suggestions, security checks, and best-practice guidance as you code.
Quick start
git clone <this-repo>
cd mcp_server
python -m venv venv
./venv/bin/pip install -r requirements.txt
./venv/bin/python code_review_mcp_server.py
With Cursor: Add the server to your MCP config (e.g. copy mcp.json into ~/.cursor/ and set workingDirectory to this repo). Cursor will then offer tools like senior_review, review_code_quality, and security_review when you work on code.
What it does
The server exposes tools over MCP that your editor can call to:
| Area | Tools |
|---|---|
| One-shot review | senior_review — checklist and concrete suggestions (naming, errors, types, tests, security, DRY) |
| Quality | review_code_quality — long functions, nesting, type hints, error handling |
| Security | security_review — eval/exec, shell/SQL injection, hardcoded secrets, permissions |
| Refactor | refactor_code — split functions, reduce complexity, unused imports, naming |
| Structure | suggest_code_split, suggest_folder_structure, suggest_reuse — split by logic, folder layout, reuse existing code |
| Tests | generate_tests — scenarios and edge cases per function |
| Static analysis | Ruff (Python), ShellCheck (Bash), ESLint (JS/TS), patch generation |
So instead of "quick AI code," you get feedback that matches what a senior engineer would expect in a code review: clear structure, fewer security risks, and maintainable patterns.
Requirements
- Python 3.10+
- Optional: Ruff for Python linting (
pip install ruff), ShellCheck for Bash, ESLint (e.g. vianpx) for JavaScript/TypeScript
Project structure
mcp_server/
main.py # Minimal entry point
code_review_mcp_server.py # Entry point with config and logging
tools/ # MCP tools (quality, security, refactor, etc.)
utils/ # Helpers (temp files, diffs)
tests/ # Unit tests (tools, utils, common)
mcp.json # Example MCP config for Cursor
requirements.txt
requirements-dev.txt # Dev deps (pytest); optional
pyproject.toml # Project metadata and pytest config
Testing
From the project root (with the venv activated and deps installed):
python -m unittest discover -s tests -p 'test_*.py' -v
Or install dev deps and use pytest: pip install -r requirements-dev.txt then pytest tests/ -v.
Usage
-
Run the server from the project directory:
./venv/bin/python code_review_mcp_server.pyor
python main.py(both use the same config and logging). -
Use from Cursor: Point your Cursor MCP config at this repo. The example
mcp.jsonuses relative paths:workingDirectoryshould resolve to the cloned repo (e.g.../mcp_serverif the config file lives in~/.cursor). For reliability, you can setworkingDirectoryto the absolute path of this repo (e.g.~/mcp_server).
Getting better results
- Pass
file_pathwhen callingsenior_review,review_code_quality, orsecurity_review. Findings will includefile:linereferences so you can jump to the exact location. - Use
focuswithsenior_reviewto narrow the checklist:"security"(secrets, injection, permissions),"api"(naming, types, docs), or omit for the full checklist. - Review in small chunks. Run review on one file or one concern at a time; large blobs of code produce noisier or vaguer feedback.
- Ask for one thing at a time. For example: “Run security_review on this file” or “Run senior_review with focus=api on this function.”
License and author
License: MIT — see LICENSE.
Author: Dmitry Troshenkov.
Contributions and feedback are welcome.
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