hpc-mcp 0.0.0

Agentic MCP tools for HPC

hpc-mcp

🌀 Agentic MCP tools for High Performance Computing

Related Projects

• flux-mcp: MCP functions for Flux Framework.
• fractale-mcp: (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.

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.

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