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Coreshub MCP Server

@coreshub

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

coreshub

Coreshub MCP Server について

mcp server for coreshub: https://coreshub.cn/

Coreshub MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-server-coreshub": {
      "command": "uv",
      "args": [
        "run",
        "src/coreshub_mcp_server"
      ]
    }
  }
}

Coreshub MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Coreshub MCP Server?

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.

How to use Coreshub MCP Server?

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.

Key features of Coreshub MCP Server

  • Query EPFS file systems and their billing info
  • Retrieve container instance details with filtering
  • Get SSH connection info for specific instances
  • List distributed training tasks with time ranges
  • Fetch detailed logs for distributed training jobs
  • Query inference services and their logs
  • Extensible architecture for custom tools and prompts

Use cases of Coreshub MCP Server

  • AI assistant that helps users manage cloud storage (EPFS) and billing
  • Automated container instance monitoring and SSH access retrieval
  • Debugging distributed training tasks by fetching logs
  • Tracking status and logs of inference services on Jishi Computing

よくある質問

1

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.

2

What environment variables are required?

You must set `QY_ACCESS_KEY_ID`, `QY_SECRET_ACCESS_KEY`, and `CORESHUB_USER_ID` with your Jishi Computing account credentials.

3

How do I install the server via Cherry Studio?

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.

4

Can I run the server locally without Cherry Studio?

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.

5

How do I add a custom tool or prompt?

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.

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