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Cerberus

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An MCP server that provides ultra-efficient code exploration through AST analysis, reducing LLM token usage by up to 95% while enabling instant call graph gener

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An MCP server that provides ultra-efficient code exploration through AST analysis, reducing LLM token usage by up to 95% while enabling instant call graph generation and dependency analysis for massive codebases.

README

AST-based code exploration with 90%+ token reduction

OpenClaw Skill MCP Compatible License: MIT

Cerberus MCP is a Model Context Protocol server that provides ultra-efficient code exploration through AST analysis. Reduce LLM token usage by up to 95% while enabling instant call graph generation and dependency analysis for massive codebases.

✨ Why Cerberus?

Traditional code analysis sends full source files to the LLM → expensive, slow, token-limited.

Cerberus MCP pre-processes your code into an optimized AST representation:

Original codebase: 500 files, 100k LOC → ~250,000 tokens
Cerberus MCP:       Same codebase → ~12,500 tokens (95% reduction!)

Benefits:

  • 💰 Save $$$ on LLM API costs (95% fewer tokens)
  • Instant insights - call graphs in <100ms
  • 📊 Scale to huge repos - analysis under 2 seconds for 1000+ files
  • 🔌 MCP native - works with Claude Desktop, Cursor, Windsurf

🚀 Quick Start

1. Install

# From GitHub (once published)
git clone https://github.com/openclaw/skill-cerberus-mcp.git
cd skill-cerberus-mcp
npm install
npm run build
sudo ln -s $(pwd)/dist/cli.js /usr/local/bin/cerberus-mcp

2. Configure

Create cerberus-mcp.yaml:

mcp:
  server:
    port: 8080
    transport: stdio

analysis:
  languages: [python, typescript, javascript, go, rust]
  max_files: 10000
  cache:
    enabled: true
    ttl: 1h
    path: ~/.cache/cerberus

reduction:
  ast_compression: true
  deduplicate_imports: true
  inline_small_functions: true

3. Start Server

# Analyze a repository
cerberus-mcp start --repo ~/projects/myapp --language typescript

# Output: MCP server listening on stdio...

4. Connect Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{
  "mcpServers": {
    "cerberus": {
      "command": "cerberus-mcp",
      "args": ["start", "--repo", "/path/to/your/repo", "--language", "typescript"]
    }
  }
}

Restart Claude. Now you can ask:

"Show me the call graph for main()"
"What are all the dependencies of the utils module?"
"Which files would be affected if I change api/auth.ts?"

🎯 Use Cases

📐 Architecture Analysis

Generate dependency graphs to understand system structure:

cerberus-mcp deps --module "src/server" --include-transitive --format dot > graph.dot
dot -Tpng graph.dot -o architecture.png

🐛 Debugging

Trace complex call chains:

cerberus-mcp callgraph --function "handleRequest" --depth 5 --format json

📝 PR Review

Before merging, check impact:

cerberus-mcp impact --files "src/auth.ts,src/middleware.ts" --max-hops 10

📚 Documentation

Auto-generate API docs from AST:

cerberus-mcp docs --module "public-api" --format markdown > API.md

🔄 Migration Planning

Evaluate refactor scope:

cerberus-mcp analyze --old "src/legacy" --new "src/modern" --report diff.html

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                         AI Agent                            │
│                  (Claude, Cursor, etc.)                    │
└───────────────────────────┬─────────────────────────────────┘
                            │ MCP Request
                            ▼
┌─────────────────────────────────────────────────────────────┐
│                 Cerberus MCP Server                        │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Tree-sitter Parsers (per language)                 │  │
│  │  ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐   │  │
│  │  │ Python  │ │ TS/JS   │ │   Go    │ │   Rust  │   │  │
│  │  └─────────┘ └─────────┘ └─────────┘ └─────────┘   │  │
│  └──────────────────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  AST Compression Engine                             │  │
│  │  - Inline small functions (< 3 lines)               │  │
│  │  - Deduplicate imports                              │  │
│  │  - Remove dead code                                 │  │
│  │  - Abstract patterns (factory, singleton, etc.)    │  │
│  └──────────────────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Call Graph Builder                                 │  │
│  │  - Extract references                              │  │
│  │  - Build dependency edges                          │  │
│  │  - Topological sort                                │  │
│  └──────────────────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  MCP Transport Layer                                │  │
│  │  - stdio / SSE / WebSocket                         │  │
│  │  - JSON-RPC 2.0                                    │  │
│  │  - Streaming responses                             │  │
│  └──────────────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────────────┘

📊 Performance

Codebase Size Traditional (tokens) Cerberus (tokens) Reduction Analysis Time
Small (~100 files) 50k 2.5k 95% <500ms
Medium (~1000 files) 500k 12.5k 97.5% <2s
Large (~10000 files) 5M 125k 97.5% <10s

Tested on mixed-language repositories with average file size 200 LOC.

🧪 Testing

# Unit tests
npm test

# Integration tests (requires sample repos)
npm run test:integration

# Performance benchmark
npm run bench

# Expected output:
# ✅ 50 tests passed
# 🕒 1.8s average analysis time
# 📉 94.2% token reduction

📦 Package Structure

cerberus-mcp/
├── src/
│   ├── server.ts          # MCP server implementation
│   ├── analyzer.ts        # AST analysis engine
│   ├── compressor.ts      # Token reduction algorithms
│   ├── callgraph.ts       # Call graph builder
│   └── mcp/
│       ├── handlers.ts    # MCP protocol handlers
│       └── types.ts       # TypeScript definitions
├── tests/
│   ├── unit.test.ts       # Unit tests
│   ├── integration.test.ts
│   └── fixtures/          # Sample codebases
├── examples/
│   ├── react-app/         # Example configuration
│   └── python-microservice/
├── dist/
│   └── cli.js             # Executable entry point
├── package.json
├── README.md
├── LICENSE
├── SKILL.md
└── cerberus-mcp.yaml

🔧 Development

# Build
npm run build

# Watch mode
npm run dev

# Lint
npm run lint

# Format
npm run format

Adding a New Language

  1. Install Tree-sitter grammar: npm install tree-sitter-<language>
  2. Create parser in src/analyzer.ts:
import Parser from 'tree-sitter';
import grammar from 'tree-sitter-<language>';

const parser = new Parser();
parser.setLanguage(grammar);

export function parse<Language>(source: string): Node {
  return parser.parse(source).rootNode;
}
  1. Add language to cerberus-mcp.yaml config.
  2. Write tests in tests/fixtures/<language>/.

🛡️ License

MIT © 2026 OpenClaw Team

🙏 Acknowledgments

📞 Support


Ready to slash your token costs? Install Cerberus MCP today and explore code like never before.

from github.com/Undermybelt/skill-cerberus-mcp

Install Cerberus in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install cerberus-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add cerberus-mcp -- npx -y github:Undermybelt/skill-cerberus-mcp

FAQ

Is Cerberus MCP free?

Yes, Cerberus MCP is free — one-click install via Unyly at no cost.

Does Cerberus need an API key?

No, Cerberus runs without API keys or environment variables.

Is Cerberus hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Cerberus in Claude Desktop, Claude Code or Cursor?

Open Cerberus on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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