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Query financial data and calculate credit-risk metrics in natural language.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "credit-risk-mcp" yet — see the docs or source repo.
Query a company’s financial data, calculate the Altman Z-Score, and explain the risk implications.
Outputs financial data, the Altman Z-Score, and a concise risk assessment.
Using this company’s financial information, estimate the loan default probability and explain the main basis.
Provides a default-probability estimate and the key indicators used.
Compare the credit-risk metrics of two companies and tell me which one is riskier.
Returns a side-by-side comparison and a conclusion on which company is riskier.
Investment or risk analysts can quickly retrieve financial data and compute risk metrics after entering a company name. It is useful for initial screening and peer comparison.
In lending workflows, users can ask for a company’s default probability or Z-Score in plain language. It helps decide whether deeper review is needed.
Students and researchers can use it to query financial data and compute common credit-risk metrics. It works well for case studies, assignments, and research notes.
It lets you query financial data in natural language and compute credit-risk metrics such as the Altman Z-Score and loan default probability.
The description explicitly mentions the Altman Z-Score and loan default probability; for any additional metrics, see the source repository.
The provided information does not specify installation steps or key requirements; for exact prerequisites, see the source repository.
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