modelscope·@TonybotNi/Doctah-MCP
暂无描述。
** 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.
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]"
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-mcpcommand 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:
cwdis the working directory, only needed in method 3, pointing to your downloaded doctah-mcp project folder
The server provides four main tools:
Search for detailed operator information:
result = await call_tool("search_operator_mcp", {
"name": "Amiya",
"sections": "skills,talents"
})
Get comprehensive enemy data:
result = await call_tool("search_enemy_mcp", {
"name": "Originium Slug",
"sections": "level0,level1"
})
Find operators matching a pattern:
result = await call_tool("list_operators_mcp", {
"name": "guard"
})
Find enemies matching a pattern:
result = await call_tool("list_enemies_mcp", {
"name": "drone"
})
Configuration file locations:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.jsonRecommended 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"
}
}
}
doctah-mcp[]/full/path/to/python["-m", "doctah_mcp.server"]/path/to/doctah-mcp-folderConfigure through environment variables:
| Variable | Purpose | Default |
|---|---|---|
| LOG_LEVEL | Logging level | INFO |
Run the test suite:
python -m pytest
Released under the MIT License. See the LICENSE file for details.
Need more detailed configuration and troubleshooting? Check out:
Made with for Arknights community
一种怀旧的虚拟宠物体验,适合人工智能时代,让你可以领养、养育并与自己的数字伙伴玩耍,该伙伴会根据你的照顾而进化。
一个服务器,允许用户与任何大语言模型对弈国际象棋,具有可视化棋盘、用标准符号进行走子以及从PGN文件分析局面的功能。
暂无描述。
暂无描述。
RandomWeb3MCP 是基于 EVM 区块哈希的随机元素生成服务。该服务提供了多种随机元素生成工具,可应用于游戏、金融、测试等领域。
暂无描述。