SciPilot

Natural language interface for scientific command-line tools via Model Context Protocol (MCP).

SciPilot bridges the gap between natural language and scientific CLI tools. Define your tool once in YAML, then let LLMs handle the rest — parameters, file paths, output parsing, the works. Works for any command-line worth talking to.

git clone https://github.com/grebenyyk/scipilot cd scipilot pip install -e . scipilot --tools-dir ./tools

- Add tool descriptors totools/(seeexamples/raspa.yaml)
- Connect MCP client (Claude Desktop, VS Code, etc.)
- Ask in natural language:

- "Run a helium void fraction calculation on MIL-47 at 298 K"
- "Compare results from yesterday's simulations"

You write a tool descriptor — a YAML file that tells SciPilot:

• What your tool expects (inputs, types, defaults) • How to build the command (templates) • Where to find the output (file paths, regex patterns) SciPilot exposes these as MCP tools that any LLM can call.

tool: name: mytool binary: mytool operations: - name: run_simulation description: "Run a simulation" inputs: - name: input_file type: file required: true outputs: - name: result path: "output.txt" extract_pattern: "Result: ([0-9.]+)"

Seeexamples/for complete tool descriptors.

⚠️Security Note: Tool YAML files execute with full shell privileges. Only load tool descriptors you trust and have reviewed. User inputs are substituted directly into shell command templates.

scipilot/ ├── server.py # MCP server entry point ├── tool_loader.py # YAML parsing, tool discovery ├── executor.py # Subprocess execution, output parsing └── models.py # Dataclasses for tool descriptors tools/ # Your tool descriptors (gitignored) examples/ # Example descriptors

# Run tests pytest # Type checking mypy scipilot/ # Format ruff format .

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