Doctah-MCP

🌍 Language / 语言选择: 🇺🇸 English | 🇨🇳 中文

🎯 Enable AI assistants to search and access Arknights game data through a simple MCP interface.

The Doctah-MCP Server provides a bridge between AI assistants and PRTS.wiki's Arknights repository through the Model Context Protocol (MCP). It allows AI models to search for operators and enemies and access their content in a programmatic way.

✨ Core Features

• 🎯 Operator Search: Query detailed operator information including skills, talents, and attributes
• ⚔️ Enemy Intelligence: Access comprehensive enemy data with level progression
• 📋 List Search: Find operators and enemies with fuzzy search functionality
• 🔍 Content Verification: Smart content validation to distinguish operators from enemies
• 🤖 AI-Friendly: Clean Markdown output with consistent structure

🚀 Quick Start

Install from Source

git clone https://github.com/TonybotNi/Doctah-MCP.git
cd doctah-mcp
pip install -e .

Verify installation:

# Test if global command works
doctah-mcp --help

# Or test with Python module
python -m doctah_mcp.server --help

For development:

# Clone and set up development environment
git clone https://github.com/TonybotNi/Doctah-MCP.git
cd doctah-mcp

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

🔌 MCP Integration

Choose one of the following configuration methods for your MCP client config file:

Method 1: Using global command (recommended)

{
    "mcpServers": {
        "doctah-mcp": {
            "command": "doctah-mcp",
            // Or use full path: "/full/path/to/doctah-mcp"
            "args": []
        }
    }
}

💡 If doctah-mcp command is not found, use Method 3 with full path to python executable

Method 2: Using Python module

{
    "mcpServers": {
        "doctah-mcp": {
            "command": "python",
            "args": ["-m", "doctah_mcp.server"]
        }
    }
}

Method 3: Using full path (most reliable)

{
    "mcpServers": {
        "doctah-mcp": {
            "command": "/full/path/to/python",
            "args": ["-m", "doctah_mcp.server"],
            "cwd": "/path/to/doctah-mcp-folder"
        }
    }
}

💡 Note: cwd is the working directory, only needed in method 3, pointing to your downloaded doctah-mcp project folder

💡 Available Tools

The server provides four main tools:

1. Operator Search

Search for detailed operator information:

result = await call_tool("search_operator_mcp", {
    "name": "Amiya",
    "sections": "skills,talents"
})

2. Enemy Search

Get comprehensive enemy data:

result = await call_tool("search_enemy_mcp", {
    "name": "Originium Slug",
    "sections": "level0,level1"
})

3. List Operators

Find operators matching a pattern:

result = await call_tool("list_operators_mcp", {
    "name": "guard"
})

4. List Enemies

Find enemies matching a pattern:

result = await call_tool("list_enemies_mcp", {
    "name": "drone"
})

📁 Client Configuration

Claude Desktop

Configuration file locations:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

Recommended configuration (simplest):

{
  "mcpServers": {
    "doctah-mcp": {
      "command": "doctah-mcp",
      "args": []
    }
  }
}

Fallback configuration (if above doesn't work):

{
  "mcpServers": {
    "doctah-mcp": {
      "command": "/full/path/to/python",
      "args": ["-m", "doctah_mcp.server"],
      "cwd": "/path/to/doctah-mcp-folder"
    }
  }
}

Cherry Studio

1. Open Cherry Studio → Settings → MCP Servers → Add
2. Select Type: STDIO
3. Simple configuration:
   • Command: doctah-mcp
   • Args: []
4. Fallback configuration (if above doesn't work):
   • Command: /full/path/to/python
   • Args: ["-m", "doctah_mcp.server"]
   • Cwd: /path/to/doctah-mcp-folder

⚙️ Configuration

Configure through environment variables:

🧪 Testing

Run the test suite:

python -m pytest

📄 License

Released under the MIT License. See the LICENSE file for details.

📖 Detailed Setup Guides

Need more detailed configuration and troubleshooting? Check out:

• Claude Desktop Detailed Setup
• Cherry Studio Detailed Setup