@PhelanShao
基本信息
An MCP (Model Context Protocol) server that acts as a wrapper around the `dpdispatcher` library. It allows language models or other MCP clients to submit and manage computational jobs on local machines or HPC clusters supported by `dpdispatcher`.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"dpdispatcher-mcp-server": {
"command": "python",
"args": [
"dispatcher_mcp_server/fast_server.py"
]
}
}
}工具列表暂未提供
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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。
An MCP (Model Context Protocol) server that wraps the dpdispatcher library, allowing language models or other MCP clients to submit and manage computational jobs on local machines or HPC clusters supported by dpdispatcher.
Install Python 3.x and the required libraries (dpdispatcher, mcp, anyio). Place the server files (fast_server.py, job_manager.py, __init__.py) in a directory (e.g., dispatcher_mcp_server). Configure dpdispatcher if needed (e.g., SSH keys for remote HPCs, Bohrium credentials). Run python dispatcher_mcp_server/fast_server.py from the parent directory. The server listens via stdio and can be integrated with MCP clients (e.g., Cline) by adding a JSON configuration block to the client’s MCP settings.
submit_job tool.query_status tool.cancel_job tool.fetch_result.It acts as a wrapper around the `dpdispatcher` library, exposing its job submission and management functions (submit, query, cancel, fetch result) as standard MCP tools for use by language models or other MCP clients.
Python 3.x is required, along with the `dpdispatcher`, `mcp`, and `anyio` libraries (all installable via pip).
If submitting to remote HPC clusters or Bohrium, ensure `dpdispatcher` itself is correctly configured (e.g., SSH keys for HPCs, Bohrium credentials). The server does not manage these credentials.
The server uses stdio transport (standard input/output). It is designed for local integration with MCP clients running in the same process environment.
Add a JSON block to your Cline MCP settings (e.g., `mcp_settings.json`) specifying the command (`python`), arguments (`dispatcher_mcp_server/fast_server.py`), the working directory, and optionally the `PYTHONPATH` environment variable. Then restart the client.
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