SwolfPy MCP quickstart

Create a landfill and waste-to-energy project, run a first LCA, inspect contributions, and clean up stored state.

First LCA

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health_check
→ get_tutorial(tutorial="first_lca")
→ list_templates
→ create_project(template="lf_wte_basic", operation_key="first-lca-v1")
→ get_project_summary(result_id=...)
→ run_lca(result_id=..., functional_unit={"baseline": 1})
→ contribution_analysis(lca_result_id=...)
→ dispose_result(lca_result_id)
→ dispose_result(project_id)

Comparisons and uncertainty

Use run_comparative_lca for functional-unit × method comparisons and run_monte_carlo for uncertainty analysis. Retrieve Monte Carlo results with get_mc_results and keep the encoded distributions with the study record.

Long-running work

Explicit async variants are available for project creation, LCA, comparative LCA, Monte Carlo, and optimization. Poll the returned job_id with get_job_status and retrieve the terminal output with get_job_result.

Note

Native MCP Tasks can also be enabled with SWOLFPY_NATIVE_TASKS_ENABLED=true for compatible clients.

Built-in documentation

The server includes offline documentation and tutorial tools, including search_documentation, get_documentation_page, get_api_reference, get_workflow_guide, and get_tutorial.