optix-mcp-server-ravn 1.0.2

MCP server for source code analysis

optix-mcp-server

MCP server for source code analysis.

Installation

Option 1: Quick Install with Wizard (Recommended)

The easiest way to install Optix MCP Server is using the installation wizard.

Prerequisites

• macOS 12+ or Ubuntu 20.04+
• curl (pre-installed on most systems)

One-Command Install

# Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh

# Run the installation wizard
uvx --from optix-mcp-server optix install

The wizard will guide you through:

1. Selecting AI agents to configure (Claude Code, Cursor, VS Code, Codex CLI, OpenCode)
2. Choosing installation scope (global or local/project)
3. Optional expert analysis setup (requires OpenAI API key)
4. Optional dashboard configuration

Wizard Options

Flag	Description
--agents <list>	Comma-separated agents: claude,cursor,codex,vscode,opencode
--scope <scope>	Installation scope: global or local
--expert	Enable expert analysis feature
--no-expert	Disable expert analysis feature
--quiet, -q	Suppress non-essential output
--verbose, -v	Enable detailed output

Examples

# Interactive mode (recommended for first-time users)
uvx --from optix-mcp-server optix install

# Non-interactive: Install for Claude Code only, global scope
uvx --from optix-mcp-server optix install --agents claude --scope global

# Enable expert analysis during installation
uvx --from optix-mcp-server optix install --expert

Verify Installation

# Check configuration status
uvx --from optix-mcp-server optix health

Option 2: Development Setup

For contributors or those who need to modify the source code.

Prerequisites

• Python 3.10 or higher (3.13.11 recommended via pyenv)
• pip or uv package manager
• Git

Clone and Setup Environment

# Clone repository
git clone <repository-url>
cd optix-mcp-server

# Setup Python version (if using pyenv)
pyenv install 3.13.11
pyenv local 3.13.11

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

Install Dependencies

# Install package with dev dependencies
pip install -e ".[dev]"

# Or with uv (recommended)
uv pip install -e ".[dev]"

Configure Environment (Optional)

For features requiring API keys (like security_audit tool with LLM expert analysis):

# Copy the example environment file
cp .env.example .env

# Edit .env and add your OpenAI API key
# Example:
# OPENAI_API_KEY=sk-...

The server automatically loads variables from .env file using python-dotenv.

Start Server

# Start with default settings (stdio transport)
python server.py

# Start with custom settings via environment variables
export SERVER_NAME=my-server
export LOG_LEVEL=DEBUG
python server.py

Quick Verification (Development)

Run this to verify your development setup is correct:

# 1. Check Python
python --version

# 2. Check dependencies
python -c "from mcp.server.fastmcp import FastMCP; print('MCP OK')"

# 3. Check tools
python -c "import server; from tools import get_available_tools; print(get_available_tools())"

# 4. Run tests
pytest tests/ -v --tb=short

Expected output: All tests pass, health_check in available tools list.

Environment Variables

Server Configuration

Variable	Default	Description
SERVER_NAME	optix-mcp-server	Server name for MCP
OPTIX_LOG_LEVEL	INFO	Logging level (DEBUG, INFO, WARN)
LOG_LEVEL	INFO	Fallback logging level if OPTIX_LOG_LEVEL not set
TRANSPORT	stdio	Transport type (stdio, sse, http)
DISABLED_TOOLS	(empty)	Comma-separated list of tools to disable

API Keys (Optional)

Required for specific features like LLM expert analysis in audit tools (security_audit, devops_audit, a11y_audit, principal_audit):

Variable	Description
OPENAI_API_KEY	OpenAI API key for GPT models

Expert Analysis Configuration

Optional settings for LLM-based expert validation of audit findings:

Variable	Default	Description
EXPERT_ANALYSIS_ENABLED	false	Enable expert LLM analysis of audit findings
EXPERT_ANALYSIS_TIMEOUT	30	Timeout for expert analysis in seconds
EXPERT_ANALYSIS_MAX_FINDINGS	50	Maximum number of findings to analyze

Note: Expert analysis requires EXPERT_ANALYSIS_ENABLED=true and a valid OPENAI_API_KEY. The expert analysis feature works with all audit tools (security_audit, devops_audit, a11y_audit, principal_audit) to provide LLM-validated assessments of findings, identify additional concerns, and prioritize remediation efforts.

Configuration via .env file (recommended):

1. Copy .env.example to .env
2. Add your API keys
3. The server automatically loads .env using python-dotenv

Logging Configuration

Setting Log Level

Control logging verbosity via the OPTIX_LOG_LEVEL environment variable:

# In .env file or shell
export OPTIX_LOG_LEVEL=DEBUG  # Most verbose - detailed execution info
export OPTIX_LOG_LEVEL=INFO   # Default - summary info
export OPTIX_LOG_LEVEL=WARN   # Warnings only

Log Output

Logs are written to:

• File: logs/optix.log (for real-time monitoring)
• Stderr: Always enabled for immediate feedback

Log format:

2026-01-18 10:30:45 - INFO - [security_audit] Step 1 completed: 3 findings

Real-Time Log Monitoring

Monitor logs in real-time while the server is running:

# All logs from all tools
./watch-logs.sh all

# Filter by specific tool
./watch-logs.sh security  # security_audit only
./watch-logs.sh a11y      # a11y_audit only
./watch-logs.sh devops    # devops_audit only
./watch-logs.sh health    # health_check only

Development Workflow

Running Tests

Note: Ensure the virtual environment is activated before running tests. If you see ModuleNotFoundError: No module named 'mcp', run source .venv/bin/activate first.

# Activate venv (if not already active)
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Full test suite
pytest tests/ -v

# Unit tests only (fast)
pytest tests/unit/ -v

# Integration tests only
pytest tests/integration/ -v

# Specific test file
pytest tests/unit/tools/test_health_check.py -v

Adding a New Tool

Tools in optix-mcp-server are MCP-agnostic, meaning they can be tested independently without MCP context.

1. Create tool directory:

   tools/
   └── my_tool/
       ├── __init__.py
       ├── core.py      # Business logic (no MCP imports)
       └── spec.md      # Documentation
   

2. Implement in core.py (no MCP imports):

   def my_tool_impl(param: str) -> dict:
       """Pure business logic."""
       return {"result": param.upper()}
   

3. Register in server.py:

   from tools.my_tool.core import my_tool_impl
   from tools import register_tool
   
   @mcp.tool()
   def my_tool(param: str) -> str:
       return json.dumps(my_tool_impl(param))
   
   register_tool("my_tool", impl=my_tool_impl, description="My tool description")
   

4. Add unit test in tests/unit/tools/test_my_tool.py:

   from tools.my_tool.core import my_tool_impl
   
   def test_my_tool_impl():
       result = my_tool_impl("hello")
       assert result["result"] == "HELLO"
   

Troubleshooting

Server won't start

1. Check Python version: python --version (needs 3.10+)
2. Verify dependencies: pip list | grep mcp
3. Check configuration:

   python -c "from config.defaults import ServerConfiguration; print(ServerConfiguration.from_env())"
   

Tests failing

1. Ensure dev dependencies installed: pip install -e ".[dev]" or uv pip install -e ".[dev]"
2. Check pytest version: pytest --version (needs 7.0+)
3. Run single test for details: pytest tests/unit/tools/test_health_check.py -v

Import errors

ModuleNotFoundError: No module named 'mcp'

• Virtual environment not activated. Run: source .venv/bin/activate
• Dependencies not installed. Run: pip install -e ".[dev]"

Other import errors

1. Ensure package is installed in editable mode: pip install -e .
2. Check PYTHONPATH includes project root
3. Verify __init__.py files exist in all packages

Configuration errors

If you see "server_name must be alphanumeric with hyphens allowed":

• Ensure SERVER_NAME environment variable uses only letters, numbers, and hyphens
• Example valid names: my-server, optix-mcp-server, server123

Project Structure

optix-mcp-server/
├── server.py              # MCP server entry point
├── config/
│   └── defaults.py        # Configuration classes
├── tools/
│   ├── __init__.py        # Tool registry
│   ├── base.py            # Tool Protocol interface
│   └── health_check/      # health_check tool
│       ├── __init__.py
│       ├── core.py        # Business logic (MCP-agnostic)
│       └── spec.md        # Tool specification
└── tests/
    ├── integration/       # Integration tests
    │   ├── conftest.py    # Test fixtures
    │   └── test_server_startup.py
    └── unit/              # Unit tests
        └── tools/
            ├── test_health_check.py
            └── test_registry.py