MCP Server Analyzer for Python ππ
MCP serverDev toolsWith this app added, your AI can review Python, JavaScript, and TypeScript code and find problems before they cause trouble. It checks for coding mistakes, type issues, and code that is no longer used, drawing on analysis tools including Ruff, ty, Vulture, and Biome. That makes it easier to keep a codebase in good shape and fix issues early.
Unavailable. This server has no hosted endpoint yet, so ahel can't serve it.
After adding it, ask your AI to check a Python, JavaScript, or TypeScript file or project you are working on. Then ask it to walk you through the issues it found and what to fix.
What your AI can do with it
- Spot mistakes and risky patterns in Python code
- Find type mistakes in Python code
- Locate unused code that can be cleaned up
- Check JavaScript and TypeScript code for problems
- Review code across Python, JavaScript, and TypeScript projects
- Report the issues it finds so you know what to fix
From the project's README
As published by anselmoo/mcp-server-analyzer in README.md.
A powerful Model Context Protocol (MCP) server that provides comprehensive Python code analysis using Ruff for linting, ty for type checking, and Vulture for dead code detection. Perfect for AI assistants, IDEs, and automated code review workflows.
π Quick Start
VS Code Integration (One-Click Install)
For quick installation, use one of the one-click install buttons below...
For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).
Optionally, you can add it to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.
Note that the
mcpkey is needed when using themcp.jsonfile.
Using uvx (recommended):
{
"mcp": {
"servers": {
"analyzer": {
"command": "uvx",
"args": ["mcp-server-analyzer"]
}
}
}
}
Using Docker:
{
"mcp": {
"servers": {
"analyzer": {
"command": "docker",
"args": ["run", "-i", "--rm", "ghcr.io/anselmoo/mcp-server-analyzer"]
}
}
}
}
Universal Installation
# Install with uvx (recommended)
uvx install mcp-server-analyzer
# Install with pip
pip install mcp-server-analyzer
# Run with Docker
docker run ghcr.io/anselmoo/mcp-server-analyzer:latest
# Install from source
git clone https://github.com/anselmoo/mcp-server-analyzer.git
cd mcp-server-analyzer
uv sync --dev
uv run mcp-server-analyzer
π Features
- π RUFF Analysis: Comprehensive Python linting with auto-fixes
- π§ ty Type Checking: Fast Python type analysis with rule-based diagnostics
- π§Ή Dead Code Detection: Find unused imports, functions, and variables with VULTURE
- β‘ Biome JS/TS Analysis: Fast linting and formatting for JavaScript and TypeScript
- π Quality Scoring: Combined analysis with quality metrics
- π FastMCP Framework: High-performance MCP server implementation
- π³ Docker Ready: Multi-architecture containers with security signing
- π Secure: All releases signed with Sigstore for supply chain security
π Analysis Examples
RUFF Linting Preview
See comprehensive linting analysis examples: π RUFF Analysis Preview
VULTURE Dead Code Detection Preview
Explore dead code detection capabilities: π§Ή VULTURE Analysis Preview
π οΈ Available Tools
| Tool | Description | Use Case |
|---|---|---|
ruff-check | Lint Python code with RUFF | Style violations, potential errors |
ruff-format | Format Python code with RUFF | Code formatting and consistency |
ruff-check-ci | CI/CD optimized RUFF output | GitHub Actions, GitLab CI |
ty-check | Type-check Python code with ty | Type safety, incorrect return values |
vulture-scan | Dead code detection | Unused imports, functions, variables |
biome-check | Lint JS/TS code with Biome | Style violations, potential errors |
biome-format | Format JS/TS code with Biome | Code formatting and consistency |
analyze-code | Combined Ruff + ty + Vulture analysis | Complete code quality assessment |
π§ Configuration
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"analyzer": {
"command": "uvx",
"args": ["mcp-server-analyzer"]
}
}
}
Zed
Add to your Zed settings.json:
"context_servers": {
"analyzer": {
"command": "uvx",
"args": ["mcp-server-analyzer"]
}
}
Claude Code (project-level)
Place .mcp.json at your project root:
{
"mcpServers": {
"analyzer": {
"command": "uvx",
"args": ["mcp-server-analyzer"]
}
}
}
π§ͺ Development
Prerequisites
Setup
# Clone repository
git clone https://github.com/anselmoo/mcp-server-analyzer.git
cd mcp-server-analyzer
# Install Python dependencies
uv sync --dev
# Install Biome (JS/TS analyzer)
npm ci
# Run tests
uv run pytest
# Run type checks
uv run ty check src tests
# Run pre-commit hooks
uv tool run pre-commit run --all-files
# Build Docker image
docker build -t mcp-server-analyzer .
Testing
# Run all tests
uv run pytest tests/ -v
# Run with coverage
uv run pytest --cov=src/mcp_server_analyzer --cov-report=html
# Test specific functionality
uv run pytest tests/test_server.py::TestAnalyzers::test_ruff_with_sample_code
π Quality Metrics
The server provides quality scoring based on:
- Ruff Issues: Style violations, potential bugs, complexity metrics
- ty Diagnostics: Static typing errors and warnings
- Dead Code Detection: Unused imports, functions, variables
- Combined Score: Weighted quality assessment (0-100)
π Security
- Signed Releases: All releases signed with Sigstore
- Container Signing: Docker images signed with Cosign
- Trusted Publishing: PyPI releases use GitHub OIDC trusted publishing
- Vulnerability Scanning: Automated security scanning in CI/CD
- Supply Chain Security: SLSA Build Level 3 compliance
- Security Policy: See SECURITY.md for vulnerability reporting
π Data Handling & Transparency
- In-memory only: Code passed to tools is written to a temporary file, analyzed, and the file is deleted immediately β nothing is persisted between calls.
- No network calls: The server makes no outbound network connections during analysis.
- No telemetry: No usage data, analytics, or crash reports are collected.
- Subprocess isolation: ruff, ty, and vulture are invoked with fixed argument lists β no shell expansion or arbitrary command execution.
π Documentation
- Full Documentation - GitHub Pages docs
- Tools Reference - Detailed tool parameters and return types
- MCP Specification - Learn about Model Context Protocol
- FastMCP Framework - High-performance MCP implementation
- Ruff Documentation - Python linter and formatter
- ty Documentation - Python type checker and language server
- Vulture Documentation - Dead code finder
π€ Contributing
Contributions are welcome! Please see CONTRIBUTING.md for details.
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes using Conventional Commits
- Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
π License
This project is licensed under the MIT License - see the LICENSE file for details.
π Acknowledgments
- Astral for RUFF and uv
- Jendrik Seipp for VULTURE
- Model Context Protocol team
- FastMCP framework
Made with β€οΈ for better Python code quality
Signals
- GitHub stars
- 11
- Forks
- 3
- Last commit
- Aug 2026
Advanced
- Delivery
- mcp-server-analyzer MCP server β your ahel gateway (mcp.ahel.ai) β every connected AI client.
- Catalog kind
- mcp-server
- Gateway key
io-github-anselmoo-mcp-server-analyzer- Source
- github.com/anselmoo/mcp-server-analyzer