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io.github.Anselmoo/mcp-server-analyzer

MCP server for Python, JavaScript, and TypeScript code analysis with Ruff, ty, Vulture, and Biome

Developer ToolsPythonv0.4.1

MCP Server Analyzer for Python πŸπŸ”

SafeSkill 92/100

CI/CD Pipeline PyPI version Python 3.13+ Docker License: MIT Code Coverage AgentSeal MCP Docs

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.

πŸš€ Quick Start

VS Code Integration (One-Click Install)

For quick installation, use one of the one-click install buttons below...

Install with UV in VS Code Install with UV in VS Code Insiders

Install with Docker in VS Code Install with Docker in VS Code Insiders

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 mcp key is needed when using the mcp.json file.

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

πŸ“‹ Features

  • πŸ” RUFF Analysis: Comprehensive Python linting with auto-fixes
  • 🧠 ty Type Checking: Fast Python type analysis with rule-based diagnostics
  • 🧹 Dead Code Detection: Find unused imports, functions, and variables with VULTURE
  • ⚑ Biome JS/TS Analysis: Fast linting and formatting for JavaScript and TypeScript
  • πŸ“Š Quality Scoring: Combined analysis with quality metrics
  • πŸš€ FastMCP Framework: High-performance MCP server implementation
  • 🐳 Docker Ready: Multi-architecture containers with security signing
  • πŸ”’ Secure: All releases signed with Sigstore for supply chain security

πŸ“ˆ Analysis Examples

RUFF Linting Preview

See comprehensive linting analysis examples: πŸ“‹ RUFF Analysis Preview

VULTURE Dead Code Detection Preview

Explore dead code detection capabilities: 🧹 VULTURE Analysis Preview

πŸ› οΈ Available Tools

ToolDescriptionUse Case
ruff-checkLint Python code with RUFFStyle violations, potential errors
ruff-formatFormat Python code with RUFFCode formatting and consistency
ruff-check-ciCI/CD optimized RUFF outputGitHub Actions, GitLab CI
ty-checkType-check Python code with tyType safety, incorrect return values
vulture-scanDead code detectionUnused imports, functions, variables
biome-checkLint JS/TS code with BiomeStyle violations, potential errors
biome-formatFormat JS/TS code with BiomeCode formatting and consistency
analyze-codeCombined Ruff + ty + Vulture analysisComplete code quality assessment

πŸ”§ 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"]
    }
  }
}

πŸ§ͺ Development

Prerequisites

  • Python 3.13+
  • uv (recommended) or pip
  • Node.js 22+ (for Biome JS/TS analysis)
  • Docker (optional)

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

πŸ“Š 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)

πŸ”’ 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

πŸ” 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.

πŸ“š Documentation

🀝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for details.

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes using Conventional Commits
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

πŸ“ License

This project is licensed under the MIT License - see the LICENSE file for details.

πŸ™ Acknowledgments


Made with ❀️ for better Python code quality

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
uvx mcp-server-analyzer

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-anselmoo-mcp-server-analyzer": {
      "command": "uvx",
      "args": [
        "mcp-server-analyzer"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

mcp-server-analyzerpypi

Compatible MCP Clients

io.github.Anselmoo/mcp-server-analyzer works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

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