Artemis-Eapil/mcp_server

🔌 Universal MCP Server for ARTEMIS

This directory contains the universal Model Context Protocol (MCP) server for ARTEMIS, enabling seamless mobile device automation inside AI IDEs and agents like Cursor, Claude Code, OpenClaw, Windsurf, and Jetski.

🏗️ Architecture

mcp_server/
├── __init__.py           # Package exports (mcp, main)
├── base.py               # Shared FastMCP instance
├── server.py             # Server entrypoint (stdio / sse)
├── rules.md              # AI Agent Testing Mindset & system prompt rules for IDEs
├── background/           # Background process execution
│   └── task_runner.py    # Subprocess runner for Artemis Agent
├── notifiers/            # Multi-environment notification adapters
│   ├── base.py           # BaseNotifier abstract class
│   ├── agentapi.py       # Jetski / Antigravity AgentAPI notifier
│   ├── webhook.py        # OpenClaw / CI / Discord / Slack webhook notifier
│   ├── desktop.py        # Native OS toast notifier
│   ├── file.py           # File audit logger
│   └── composite.py      # Multi-channel notification dispatcher
├── tools/                # Modular standard MCP tools
│   ├── task_runner.py    # mobile_run_task
│   ├── task_manager.py   # mobile_manage_task
│   ├── device_state.py   # mobile_get_device_state
│   └── inspect_trace.py  # mobile_inspect_trace
└── utils/                # Environment, device, and trace utilities
    ├── device_utils.py   # Cross-platform ADB and emulator resolver
    ├── env_utils.py      # Python interpreter and process manager
    └── trace_store.py    # Traces directory and status manager

🧠 AI Agent Behavioral Rules (rules.md)

When connecting ARTEMIS to AI coding assistants like Claude Code, Cursor, or Windsurf, providing the assistant with domain-specific testing discipline is critical for generating reliable test code.

The included rules.md file contains the Mobile Testing Mindset (ARTEMIS Integration) guideline. It teaches the AI agent how to properly collaborate with ARTEMIS:

1. The Runnable Code Principle & Active Exploration: Instructs the AI to never guess or hallucinate UI transitions. Instead, it must first explore the live app via ARTEMIS MCP tools (mobile_run_task, etc.) to discover and verify real-world interaction paths before writing test scripts.
2. Flash vs. Pro Routing Strategy: Guides the AI to choose Flash for rapid, straightforward UI actions (< 30 steps) and Pro for complex multi-agent planning, polling loops, or video/log diagnosis.
3. Latency & Timing Compensation: Clarifies the difference between AI exploratory latency (e.g., model decision intervals) and the deterministic timing requirements of final test code.
4. "Dynamic-First, Coordinate-Fallback" Locator Pattern: Teaches the AI to prioritize dynamic UI locators (Resource IDs, OCR text, semantics) for layout resilience, while implementing absolute coordinate fallbacks for maximum execution reliability.

How to Apply rules.md in Your IDE

• Claude Code: Copy or include the contents of rules.md in your project's CLAUDE.md file (or reference it directly in your instructions).
• Cursor: Copy the contents of rules.md into your .cursorrules or create a new rule file in .cursor/rules/artemis.mdc.
• Windsurf / OpenClaw: Add the rules to your global/workspace rules or agent system prompts so the assistant always follows verified mobile testing principles.

🛠️ MCP Tools Overview

• mobile_run_task: Asynchronously launches an autonomous mobile automation task (Flash or Pro model).
• mobile_manage_task: Manages task lifecycle (status, stop, inject_instruction).
• mobile_get_device_state: Real-time observer (screenshot or OCR+XML hierarchy).
• mobile_inspect_trace: Granular trace inspection, visual action overlays, and agent reasoning.

🚀 How to Run & Configure

CLI Execution

# Start server over stdio
python -m mcp_server

# Or via Artemis CLI
artemis mcp

IDE Configuration

Run artemis mcp --generate-config all to generate ready-to-use configuration JSON for Cursor, Claude Code, OpenClaw, and Windsurf.