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Hpc

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Provides MCP tools for high-performance computing (HPC) and converged computing, enabling agentic interactions with HPC resources and workflows.

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Описание

Provides MCP tools for high-performance computing (HPC) and converged computing, enabling agentic interactions with HPC resources and workflows.

README

🌀 Agentic MCP tools for High Performance Computing

PyPI version DOI

img/hpc-mcp.png

Related Projects

  • flux-mcp: MCP functions for Flux Framework.
  • fractale: (fractale) MCP orchestration (agents, databases, ui interfaces).

Usage

This is a library of MCP tools (functions, prompts, and resources) intended for converged computing and HPC use cases. A demo server is provided here, and largely functions are expected to be used a-la-carte as imports to other libraries. We welcome contributions of all functions types that are related to HPC, converged computing, and science. These MCP tools can be used via a standalone server, or combined with other tools.

Environment

Control of tools (access, limits, etc.) is done by way of the environment.

Name Description Default
HPCMCP_FILESYSTEM_SANDBOX enable (require) a sandbox False
HPCMCP_FILESYSTEM_DATA_ROOT if sandbox enabled, read-only data root unset
HPCMCP_FILESYSTEM_RESULT_ROOT if sandbox enabled, read and write result root for agent to write unset
HPCMCP_FILESYSTEM_TOKEN_LIMIT Hard limit of tokens to allow in response unset

Server

We provide examples for fastmcp and a vanilla mcp (stdio) setup. Neither requirements are added to the install directly, so it's up to the user (you) to install. Tests are performed with fastmcp (TBA)

fastmcp

You will need fastapi and fastmcp installed.

# fastmcp
pip install fastmcp fastapi

To start the demo server:

# Vanilla MCP (with cli)
echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "test", "version": "1.0"}}}' | python3 -m hpc_mcp.server | jq

# Initialize and list tools
(echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "manual-test", "version": "1.0"}}}';
 echo '{"jsonrpc": "2.0", "method": "notifications/initialized"}';
 echo '{"jsonrpc": "2.0", "id": 2, "method": "tools/list"}') | python3 -m hpc_mcp.server | jq

# FastMCP
python3 -m hpc_mcp.server.fastmcp

Testing

I will add tools to git as I write tests for them. To test, start the fastmcp server in one terminal:

python3 -m hpc_mcp.server.fastmcp

In another terminal, run the test. You'll need to pip install pytest pytest-asyncio

pytest -xs tests/test_build_docker.py

# or
pytest -xs tests/test_*.py

TODO

  • Add annotated descriptions to all functions for LLM.

Tools to add:

  • helpers
    • debug
    • result parser (regular expressions)
  • kubernetes
    • deploy job
    • deploy minicluster

License

DevTools is distributed under the terms of the MIT license. All new contributions must be made under this license.

See LICENSE, COPYRIGHT, and NOTICE for details.

SPDX-License-Identifier: (MIT)

LLNL-CODE- 842614

from github.com/converged-computing/hpc-mcp

Установка Hpc

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/converged-computing/hpc-mcp

FAQ

Hpc MCP бесплатный?

Да, Hpc MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Hpc?

Нет, Hpc работает без API-ключей и переменных окружения.

Hpc — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Hpc в Claude Desktop, Claude Code или Cursor?

Открой Hpc на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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