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Query relational predictive analytics with graph management and natural-language-to-PQL conversion.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "KumoRFM MCP Server" yet — see the docs or source repo.
Convert this request into a KumoRFM-compatible PQL query: predict the top 100 high-value customers most likely to churn in the next 30 days, ranked by churn probability.
An executable PQL query with the prediction target, filters, time window, and ranking logic clearly defined.
Using the current relational data, find which users are most likely to purchase a new product next week and return user IDs, prediction scores, and key related factors.
A ranked list of candidate users with prediction scores and key influencing information for analysis.
List the main entities, relationships, and connections in the current graph, and identify any missing links that could hurt prediction quality.
An overview of the graph structure, entity-relationship explanations, and recommendations for missing or fixable data links.
Query, analyze, and optionally update Odoo ERP data from Claude.
Search, validate, and cross-reference structured Markdown knowledge vaults for AI workflows.
Let AI query multiple SQL databases read-only and export results.
Search the web, research deeply, extract content, and get real-time AI answers.
Query Azure Data Explorer in natural language without writing KQL.
Connect AI to SQL Server for querying, schema exploration, reports, and charts.