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Doctah-MCP

modelscope·@TonybotNi/Doctah-MCP

games-and-gamification0下载LocalModelScope

简介

暂无描述。

MCP Server 详情

来自 ModelScope 索引
<div align="center"> <img src="./assets/images/doctah-mcp-logo.png" alt="Doctah-MCP Logo" width="150" height="150">

Doctah-MCP

License: MIT Python 3.10+ MCP

** Language / 语言选择:** English | 中文

</div>

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:

VariablePurposeDefault
LOG_LEVELLogging levelINFO

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

<div align="center">

Made with for Arknights community

GitHub Star History

Star History Chart

</div>

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自动安装

点击按钮会唤起 PolarBear 客户端,并把当前 MCP Server 的 Markdown 详情文档地址传给客户端。

/api/mcps/tonybotni-doctah-mcp/markdown
打开 PolarBear 安装查看 Markdown 文档

手动安装

在 PolarBear 或其他支持 MCP 的客户端中,新建 MCP Server,并参考下方来源或安装提示配置。

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

基本信息

分类
games-and-gamification / search / documentation-access
运行方式
No
许可证
MIT License
详情文件
tonybotni-doctah-mcp.md