lcf-strain-life

An AI-agent-native toolkit for fatigue analysis of materials. It is a Python library plus an MCP server, so AI agents can run the whole analysis by calling tools.

Provide your own strain-controlled fatigue test data and get the standardized reduction, fitted material constants, life predictions, and plots. Results are reproducible and are saved for recall.

Why this exists: plenty of fatigue software exists, but none is built for AI agents to drive directly. The agent-native design over MCP is the point. Every capability is reachable through tools an agent can call.

Convention: all analysis uses true stress and true strain. Engineering input is converted at ingestion. The fatigue exponents b and c are negative throughout.

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What it does

Stage	What happens
Ingest and normalize	raw time, strain, force plus parameters become true stress-strain
Cycle reduction	peak and valley per cycle, half-life cycle, cycles-to-failure N_f
Per-cycle metrics	stress amplitude, plastic strain amplitude, mean stress, T/C ratio, hysteresis energy
Strain-life fits	Basquin, Coffin-Manson, Ramberg-Osgood, transition life
Mean stress	Morrow, modified Morrow, SWT, Walker corrections
Save and recall	results persisted per test or material, recalled without recomputation

The toolkit is general purpose and material agnostic. It focuses on strain-life and per-cycle evolution, which the established stress-based high-cycle libraries such as pyLife, py-fatigue, and fatpack do not cover. It is input compatible with their pandas data shapes.

Install

python -m venv .venv
.venv\Scripts\activate            # Windows
pip install -e ".[mcp,dev]"

Requires Python 3.11 or newer.

Quick start, library

import lcf

# fit strain-life constants from per-test reduced data, here SAE 1137
fit = lcf.fit_strain_life(
    total_strain_amp=[0.009, 0.007, 0.005, 0.003, 0.002, 0.00175],
    stress_amp=[553, 522, 464, 405, 350, 319],         # MPa, half-life
    reversals=[4234, 7398, 14768, 77104, 437498, 3327958],
    E=208000,                                           # MPa
    min_plastic_strain=5e-4,   # exclude near-runout points from the plastic branch
)
print(fit.coffin_manson.eps_f, fit.coffin_manson.c)   # about 1.11, -0.62
print(fit.basquin.sigma_f, fit.basquin.b)             # about 1073 MPa, -0.084
print(fit.transition_reversals)                        # about 22,000 reversals

Quick start, MCP server

lcf-mcp                # runs the stdio MCP server
# or
python -m lcf

Register with Claude Code or Claude Desktop over stdio:

{ "mcpServers": {
    "lcf": { "command": "lcf-mcp" } } }

Documentation

• docs/reference holds the equations, symbols, and physics.
• docs/design/WORKFLOW.md describes the data flow and the compute, save, recall model.
• docs/decisions holds the Architecture Decision Records, one per major design choice.
• CHANGELOG.md is the chronological log of changes.
• CLAUDE.md holds the rules and positioning for AI agents working on the repo.

Project layout

src/lcf/            core library and MCP server
tests/              unit tests including golden-value validation, SAE 1137
docs/reference/     equations, physics, symbol tables
docs/design/        workflow and research-derived implementation reference
docs/decisions/     ADRs, the decision log

License

MIT. See LICENSE.