mcp-review-pr
An MCP server for multi-language PR review with deterministic analysis, providing AI-powered code review tools that detect languages, apply review guidelines, and run quality checks.
README
mcp-review-pr
An MCP (Model Context Protocol) server for multi-language PR review with deterministic analysis. It provides AI-powered code review tools that automatically detect languages, apply relevant review guidelines, and run quality checks on your pull requests.
✨ Features
- Skill-Based Architecture — Modular review skills that auto-activate based on file types, path patterns, and content detection
- Deterministic Quality Checks — Run linters and tests as part of the review pipeline, not just AI suggestions
- Impact Analysis — Classify changes by architectural layer (UI, domain, infra, shared) and detect breaking changes
- Smart Diff Chunking — Automatically splits large PRs into prioritized chunks for incremental review
- Result Caching — Cache diff results and guidelines keyed by commit SHA for fast re-runs
- Custom Rules — Layer project-specific rules on top of skill-provided guidelines via a simple
rules.mdfile - Configurable — Tune behavior with
.mcp.config.json(ignored files, risk thresholds, max diff size, etc.)
📦 Built-in Skills
| Skill | Priority | Activates On | Linter |
|---|---|---|---|
| Security | 15 | .ts, .js, .tsx, .jsx, .mjs + api/, auth/, middleware/ paths |
— |
| React | 10 | .tsx, .jsx + React imports + components/, pages/, app/ paths |
ESLint |
| TypeScript | 8 | .ts, .mts, .cts |
ESLint |
| Clean Architecture | 7 | .ts, .js, .tsx, .jsx + domain/, usecases/, services/, repositories/, etc. |
— |
| JavaScript | 5 | .js, .mjs, .cjs |
ESLint |
Skills are activated automatically when PR diffs match their criteria. Multiple skills can be active simultaneously — their guidelines and rules are merged by priority.
🛠 MCP Tools
The server exposes the following tools via the MCP protocol:
| Tool | Description |
|---|---|
get_pr_diff |
Get structured file diffs with additions, deletions, and change types |
analyze_impact |
Classify changes by layer, detect breaking changes, assign risk level |
list_skills |
List all available skills and which ones are active for the current PR |
get_skill_guidelines |
Get merged review guidelines from all active skills + custom rules |
load_rules |
Load all applicable rules (skill rules + custom repo rules) |
run_quality_checks |
Run skill linters and test suites, returns lint issues and test results |
generate_review |
Full structured PR review combining all tools into a comprehensive ReviewOutput |
🚀 Getting Started
Prerequisites
- Node.js ≥ 18
- npm
Installation
npm install
Build
npm run build
Running as MCP Server
Start the server over stdio transport (for integration with MCP-compatible clients):
# Using the compiled output
npm start
# Or during development
npm run dev
Then configure your MCP client to connect via stdio. For example, in your MCP client config:
{
"mcpServers": {
"review-pr": {
"command": "node",
"args": ["/path/to/mcp-review-pr/dist/server.js"]
}
}
}
Running as CLI
The CLI provides standalone usage without an MCP client:
# Review the current repository
npx mcp-review
# Compare against a specific branch
npx mcp-review --base develop
# List available skills and which are active
npx mcp-review --mode skills
# Show active guidelines for your PR
npx mcp-review --mode guidelines
# Analyze impact only
npx mcp-review --mode impact
# Output as markdown instead of JSON
npx mcp-review --format markdown
# Use custom skills directory
npx mcp-review --skills-dir ./my-skills
CLI Options
| Option | Alias | Description | Default |
|---|---|---|---|
--repo <path> |
-r |
Repository path | Current directory |
--base <branch> |
-b |
Base branch to diff against | main |
--skills-dir <path> |
-s |
Custom skills directory | Built-in skills |
--format <type> |
-f |
Output format: json or markdown |
json |
--mode <mode> |
-m |
Mode: review, skills, guidelines, impact, server |
review |
--help |
-h |
Show help | — |
⚙️ Configuration
Create a .mcp.config.json in your repository root to customize behavior:
{
"productionBranches": ["main", "production"],
"maxDiffLines": 5000,
"failOnRiskLevel": "high",
"ignoreFiles": ["package-lock.json", "yarn.lock", "pnpm-lock.yaml"],
"enableCaching": true
}
| Option | Type | Default | Description |
|---|---|---|---|
productionBranches |
string[] |
["main", "production"] |
Branches considered production |
maxDiffLines |
number |
5000 |
Max diff lines per review chunk |
failOnRiskLevel |
string |
"high" |
Risk level threshold to flag |
ignoreFiles |
string[] |
Lock files | Files to exclude from review |
enableCaching |
boolean |
true |
Enable diff/guideline caching |
Custom Rules
Add a rules.md file to your repository root with project-specific review rules:
- All API endpoints must validate input with Zod schemas
- Database queries must use parameterized statements
- Components must have display names for debugging
These rules are merged with skill-provided rules during review.
🧩 Creating Custom Skills
Skills are directories containing three files. Place them in the skills/ directory (or a custom directory via --skills-dir):
skills/
└── my-skill/
├── skill.json # Manifest (required)
├── guideline.md # Review guidelines
└── rules.md # Checklist rules
skill.json — Manifest
{
"name": "my-skill",
"description": "Description of what this skill reviews",
"version": "1.0.0",
"filePatterns": ["**/*.py"],
"activateOn": {
"extensions": [".py"],
"fileContains": ["import django"],
"pathPatterns": ["views/", "models/"]
},
"priority": 8,
"linter": {
"command": "npx",
"args": ["pylint", "--output-format", "json"],
"fileExtensions": [".py"]
}
}
| Field | Required | Description |
|---|---|---|
name |
✅ | Unique skill identifier |
description |
— | Human-readable description |
version |
— | Semantic version |
filePatterns |
— | Glob patterns for relevant files |
activateOn |
✅ | Activation criteria (see below) |
priority |
— | Higher = evaluated first (default: 0) |
linter |
— | Optional linter configuration |
Activation criteria (any match triggers activation):
extensions— File extensions in the diff (e.g.,[".ts", ".tsx"])fileContains— Strings found in diff content (e.g.,["from 'react'"])pathPatterns— Path substrings in changed files (e.g.,["components/"])
guideline.md — Review Guidelines
Free-form markdown that provides context and best practices for the reviewer. This is included in the review context when the skill is active.
rules.md — Review Rules
A markdown list of specific, checkable rules:
- Use strict type annotations, avoid `any`
- Prefer `const` over `let` where possible
- All exported functions must have JSDoc comments
🏗 Architecture
src/
├── server.ts # MCP server — registers all tools
├── cli.ts # CLI entry point with argument parsing
├── config.ts # .mcp.config.json loader
├── types.ts # Shared TypeScript types
├── cache.ts # Diff and guideline caching (SHA-keyed)
├── chunker.ts # Smart diff chunking with priority ordering
├── retry.ts # Exponential backoff utility
├── skills/
│ ├── index.ts # Public API re-exports
│ ├── types.ts # Skill manifest & runtime types
│ ├── loader.ts # Skill discovery, activation, guideline/rule loading
│ └── runner.ts # Skill linter execution
└── tools/
├── diff.ts # Git diff extraction via simple-git
├── impact.ts # Change impact & risk analysis
├── quality.ts # Lint + test orchestration
├── review.ts # Structured review generation
└── rules.ts # Custom rules.md loader
📜 Scripts
| Script | Description |
|---|---|
npm run build |
Compile TypeScript to dist/ |
npm run dev |
Run in development mode (via tsx) |
npm start |
Start the compiled MCP server |
npm test |
Run tests (Vitest) |
npm run test:watch |
Run tests in watch mode |
npm run typecheck |
Type-check without emitting |
npm run lint |
Lint source files with ESLint |
📄 License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.