MCP 服务器

Doctah-MCP

Enables AI assistants to search and access Arknights game data including operator information, enemy intelligence, skills, talents, and attributes through PRTS.wiki integration. Provides fuzzy search functionality for operators and enemies with clean Markdown output.

README

Doctah-MCP

🌍 Language / 语言选择: 🇺🇸 English | 🇨🇳 中文

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🎯 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

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