PluginBench
MCP Server
Maintained
MIT

io.github.Anselmoo/mcp-server-analyzer MCP Server

io.github.Anselmoo/mcp-server-analyzer

Comprehensive Python, JavaScript, and TypeScript code analysis with Ruff, ty, Vulture, and Biome.

What is the io.github.Anselmoo/mcp-server-analyzer MCP server?

The MCP Server Analyzer is an MCP server that provides comprehensive code analysis for Python, JavaScript, and TypeScript using Ruff for linting, ty for type checking, Vulture for dead code detection, and Biome for JS/TS analysis. It integrates with AI assistants, IDEs, and automated code review workflows to deliver quality scoring and actionable insights.

This server enables AI assistants and development tools to analyze code quality across multiple languages. It combines Python linting (Ruff), type checking (ty), dead code detection (Vulture), and JavaScript/TypeScript analysis (Biome) into a unified interface. Use it to catch style violations, type errors, unused code, and formatting issues automatically.

How to install io.github.Anselmoo/mcp-server-analyzer

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "mcp-server-analyzer": {
      "command": "uvx",
      "args": [
        "mcp-server-analyzer"
      ]
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • ruff-check — Lint Python code with RUFF to identify style violations and potential errors
  • ruff-format — Format Python code with RUFF for consistency
  • ruff-check-ci — CI/CD optimized RUFF output for GitHub Actions and GitLab CI
  • ty-check — Type-check Python code with ty for type safety and incorrect return values
  • vulture-scan — Detect dead code including unused imports, functions, and variables
  • biome-check — Lint JavaScript and TypeScript code with Biome
  • biome-format — Format JavaScript and TypeScript code with Biome
  • analyze-code — Combined analysis using Ruff, ty, and Vulture for complete code quality assessment

Use cases

  • Automatically lint and format Python code to catch style violations and potential bugs
  • Detect unused imports, functions, and variables in Python projects
  • Type-check Python code to identify type safety issues before runtime
  • Lint and format JavaScript and TypeScript files in mixed-language projects
  • Generate quality scores and metrics for code review workflows
  • Integrate code analysis into CI/CD pipelines with optimized output formats

io.github.Anselmoo/mcp-server-analyzer MCP server FAQ

What is the MCP Server Analyzer?

It's an MCP server that provides comprehensive code analysis for Python, JavaScript, and TypeScript using Ruff, ty, Vulture, and Biome. It integrates with AI assistants and IDEs to identify linting issues, type errors, dead code, and formatting problems.

Is it free?

Yes, the MCP Server Analyzer is open-source and licensed under the MIT License. It's free to use, modify, and distribute.

How do I install it in Claude Desktop?

Add this to your claude_desktop_config.json: {"mcpServers": {"analyzer": {"command": "uvx", "args": ["mcp-server-analyzer"]}}}

How do I install it in VS Code?

Use the one-click install buttons in the README, or manually add the configuration to your User Settings (JSON) or .vscode/mcp.json file with either uvx or Docker.

Does it require authentication or API keys?

No, the server makes no outbound network connections and requires no authentication. All analysis is performed locally.

What languages does it support?

Python (via Ruff, ty, and Vulture) and JavaScript/TypeScript (via Biome). It can analyze mixed-language projects in a single call.

README (reference)

Source of truth, from the repository.

MCP Server Analyzer for Python 🐍🔍

<!-- mcp-name: io.github.Anselmoo/mcp-server-analyzer -->

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.

🚀 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

📋 Features

  • 🔍 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
  • 📊 Quality Scoring: Combined analysis with quality metrics
  • 🚀 FastMCP Framework: High-performance MCP server implementation
  • 🐳 Docker Ready: Multi-architecture containers with security signing
  • 🔒 Secure: All releases signed with Sigstore for supply chain security

📈 Analysis Examples

RUFF Linting Preview

See comprehensive linting analysis examples: 📋 RUFF Analysis Preview

VULTURE Dead Code Detection Preview

Explore dead code detection capabilities: 🧹 VULTURE Analysis Preview

🛠️ 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

🔧 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"]
    }
  }
}

🧪 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

📊 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)

🔒 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

🔍 Data Handling & Transparency

  • In-memory only: Code passed to tools is written to a temporary file, analyzed, and the file is deleted immediately — 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 — no shell expansion or arbitrary command execution.

📚 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

📝 License

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

🙏 Acknowledgments


Made with ❤️ for better Python code quality

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