zipline-supply-chain
Enables natural-language supply-chain analysis over synthetic datasets through governed SQL/Python tools, providing supplier scorecards, forecast accuracy, risk detection, landed-cost comparisons, capacity planning, and quality trend insights without the LLM performing quantitative calculations.
- Score
- Unranked
- Evidence
- No signals yet
- Last commit
- as last read from GitHub; most reads are from 2 Sep 2026 or later
- Listed
Install
No one-command install. Set it up from its source.
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What it is
Enables natural-language supply-chain analysis over synthetic datasets through governed SQL/Python tools, providing supplier scorecards, forecast accuracy, risk detection, landed-cost comparisons, capacity planning, and quality trend insights without the LLM performing quantitative calculations.
When to use it
Enables natural-language supply-chain analysis over synthetic datasets through governed SQL/Python tools, providing supplier scorecards, forecast accuracy, risk detection, landed-cost comparisons, capacity planning, and quality trend insights without the LLM performing quantitative calculations.
How to install / invoke
See Glama for the install config.
Notes
Listed from the Glama MCP registry.