What are the prerequisites to run Coreshub MCP Server?
Python and `uv` must be installed. For best tool calling, a model with 32B parameters or higher is recommended.
@coreshub
基本信息
mcp server for coreshub: https://coreshub.cn/
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-coreshub": {
"command": "uv",
"args": [
"run",
"src/coreshub_mcp_server"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Coreshub MCP Server is a Model Context Protocol server that enables AI assistants to interact with the Jishi Computing (基石智算) cloud platform. It provides tools for managing EPFS file systems, container instances, distributed training jobs, inference services, and their logs. It is designed for developers using MCP-compatible clients such as Cherry Studio.
Install via uvx coreshub-mcp-server or clone from GitHub and run with uv run coreshub-mcp-server. Configure environment variables QY_ACCESS_KEY_ID, QY_SECRET_ACCESS_KEY, and CORESHUB_USER_ID with your Jishi Computing credentials. In Cherry Studio, add an MCP server with stdio type and the appropriate command for your OS. For CLI usage, run uv run src/coreshub_mcp_server with optional flags like --debug.
Python and `uv` must be installed. For best tool calling, a model with 32B parameters or higher is recommended.
You must set `QY_ACCESS_KEY_ID`, `QY_SECRET_ACCESS_KEY`, and `CORESHUB_USER_ID` with your Jishi Computing account credentials.
Add an MCP server with `"type": "stdio"`, command `uvx` and args `["coreshub-mcp-server"]` (or a GitHub source). Include the three environment variables in the `env` object.
Yes. Clone the repository, set the environment variables, and run `uv run src/coreshub_mcp_server` from the project root. Use the `--debug` flag for verbose output.
Create a Python file in the `plugins/` directory, implement a subclass of `BaseTool` or `BasePrompt`, and call the `register()` method. Follow the example provided in the development section.

Model Context Protocol Servers
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