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Query governed insurance metrics safely through a trusted semantic layer for AI.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "horizon-mcp-demo" yet — see the docs or source repo.
Use horizon-mcp-demo to query the predefined core metrics in the auto insurance dataset. Return total premium, claim amount, and loss ratio, and cite the metric definitions used.
Returns metric results computed from the predefined semantic layer and explains the governed definitions behind them.
Using horizon-mcp-demo, break down the predefined loss ratio metric for the last four quarters by state and line of business, using only available dimensions and read-only data sources.
Outputs a quarterly metric table grouped by state and line of business, constrained by governed query rules.
I want to verify whether 'retention rate' is a valid metric in this dataset. Use horizon-mcp-demo to check whether it exists as a predefined metric; if not, do not infer it and simply state that it is unavailable.
Clearly states whether the metric is predefined; if not, it refuses to guess and marks it as unavailable.
Adds semantic understanding and policy-gated SQL Server access for AI agents.
Define, validate, and visualize semantic metrics with trust scoring and BI integrations.
Safely let AI inspect database schemas and query PostgreSQL and MySQL data.
Securely query and analyze multiple databases with natural language across systems.
Lets AI safely explore SQL schemas and run read-only database queries.
Query commerce metrics like orders, carts, and returns with AI agents.