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# Clone and install
git clone https://github.com/IBM/AssetOpsBench.git
cd AssetOpsBench
pip install -e .
# Try a scenario (to be enabled)
python -m assetopsbench.run --scenario "List all sensors of Chiller 6 in MAIN site"
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[!NOTE] Active development is on
main. The codebase used for various publication venues continues to be maintained on separate branches, for example, ACL 2026IndustryAssetEQAand prior experimental work is maintained onmain-0.x.
AssetOpsBench is a unified framework for developing, orchestrating, and evaluating domain-specific AI agents in industrial asset operations and maintenance. It provides reproducible scenarios, agent tooling, and evaluation pipelines for multi-step workflows in simulated industrial environments.
| MCP Servers | Important tools |
|---|---|
| IoT | get_sites, get_history, get_assets, get_sensors |
| FMSR | get_failure_modes, generate_failure_modes, add_failure_modes, generate_failure_mode_sensor_mapping |
| TSFM | forecasting, timeseries_anomaly_detection |
| WO | get_work_order_distribution, predict_next_work_order, ... |
| Vibration | compute_fft_spectrum, compute_envelope_spectrum, ... |
| ... | ... |
The src/ directory contains MCP servers and a plan-execute runner built on the Model Context Protocol. See INSTRUCTIONS.md for setup.