🦡 codebadger

A containerized Model Context Protocol (MCP) server providing static code analysis using Joern's Code Property Graph (CPG) technology with support for Java, C/C++, JavaScript, Python, Go, Kotlin, C#, Ghidra, Jimple, PHP, Ruby, and Swift.

Prerequisites

Before you begin, make sure you have:

• Docker and Docker Compose installed
• Python 3.10+ (Python 3.13 recommended)
• pip (Python package manager)

To verify your setup:

docker --version
docker-compose --version
python --version

Quick Start

1. Install Python Dependencies

# Create a virtual environment (optional but recommended)
python -m venv venv

# Install dependencies
pip install -r requirements.txt

2. Start the Docker Services (Joern)

docker compose up -d

This starts:

• Joern Server: Static code analysis engine (runs CPG generation and queries)

Verify services are running:

docker compose ps

3. Start the MCP Server

# Start the server
python main.py &

The MCP server will be available at http://localhost:4242.

4. Stop All Services

# Stop MCP server (Ctrl+C in terminal)

# Stop Docker services
docker-compose down
# Optional: Clean up everything
bash cleanup.sh

Cleanup Script

Use the provided cleanup script to reset your environment:

bash cleanup.sh

This will:

• Stop and remove Docker containers
• Kill orphaned Joern/MCP processes
• Clear Python cache (__pycache__, .pytest_cache)
• Optionally clear the playground directory (CPGs and cached codebases)

Integrations

GitHub Copilot Integration

Edit the MCP configuration file for VS Code (GitHub Copilot):

Path:

~/.config/Code/User/mcp.json

Example configuration:

{
  "inputs": [],
  "servers": {
    "codebadger": {
      "url": "http://localhost:4242/mcp",
      "type": "http"
    }
  }
}

---

Claude Code Integration

To integrate codebadger into Claude Desktop, edit:

Path:

Claude → Settings → Developer → Edit Config → claude_desktop_config.json

Add the following:

{
  "mcpServers": {
    "codebadger": {
      "url": "http://localhost:4242/mcp",
      "type": "http"
    }
  }
}

Available Tools

Core Tools

Tool	Description
generate_cpg	Generate a CPG for a codebase (from local path or GitHub URL)
get_cpg_status	Get status and existence of a CPG by codebase_hash
run_cpgql_query	Execute raw CPGQL queries
get_cpgql_syntax_help	Get CPGQL syntax documentation and examples

Code Browsing Tools

Tool	Description
get_codebase_summary	Get high-level codebase overview (files, methods, calls)
list_files	List source files in the codebase
list_methods	Discover methods/functions with optional filtering
list_calls	Find function call relationships
list_parameters	Get parameter information for a method
get_method_source	Retrieve method source code
get_code_snippet	Retrieve code snippets by file and line range
get_call_graph	Build call graphs (incoming/outgoing)

Semantic Analysis Tools

Tool	Description
get_cfg	Get control flow graph (nodes AND edges) for a method
get_type_definition	Get struct/type definition with members
get_macro_expansion	Detect potential macro calls using heuristics

Taint Analysis Tools

Tool	Description
find_taint_sources	Locate external input points (getenv, malloc, read, etc.)
find_taint_sinks	Locate dangerous sinks (memcpy, system, free, etc.)
find_taint_flows	Find dataflow paths (source→sink, source-only, or sink-only)
get_variable_flow	Track variable assignments and data dependencies

Advanced Analysis Tools

Tool	Description
get_program_slice	Build backward program slices from a call
find_bounds_checks	Find bounds checks near buffer accesses

Contributing & Tests

Thanks for contributing! Here's a quick guide to get started with running tests and contributing code.

Prerequisites

• Python 3.10+ (3.13 is used in CI)
• Docker and Docker Compose (for integration tests)

Local Development Setup

1. Create a virtual environment and install dependencies

python -m venv venv
pip install -r requirements.txt

2. Start Docker services (for integration tests)

docker-compose up -d

3. Run unit tests

pytest tests/ -q

4. Run integration tests (requires Docker Compose running)

# Start MCP server in background
python main.py &

# Run integration tests
pytest tests/integration -q

# Stop MCP server
pkill -f "python main.py"

5. Run all tests

pytest tests/ -q

6. Cleanup after testing

bash cleanup.sh
docker-compose down

Code Contributions

Please follow these guidelines when contributing:

1. Follow repository conventions
2. Write tests for behavioral changes
3. Ensure all tests pass before submitting PR
4. Include a clear changelog in your PR description
5. Update documentation if needed

Configuration

The MCP server can be configured via environment variables or config.yaml.

Environment Variables

Key settings (optional - defaults shown):

# Server
MCP_HOST=0.0.0.0
MCP_PORT=4242

# Joern
JOERN_BINARY_PATH=joern
JOERN_JAVA_OPTS="-Xmx4G -Xms2G -XX:+UseG1GC -Dfile.encoding=UTF-8"

# CPG Generation
CPG_GENERATION_TIMEOUT=600
MAX_REPO_SIZE_MB=500

# Query
QUERY_TIMEOUT=30
QUERY_CACHE_ENABLED=true
QUERY_CACHE_TTL=300

Config File

Create a config.yaml from config.example.yaml:

cp config.example.yaml config.yaml

Then customize as needed.