Query BigQuery, Snowflake, Redshift & Azure Synapse with natural language
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Scored across 29 tools
Most tools have clearly distinct purposes, but there is some overlap between schema discovery tools like get_schema_context and list_prebuilds. However, descriptions provide enough clarity to distinguish them, and the majority of tools (e.g., use case CRUD, dashboard management) are well-separated.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., collect_feedback, create_aggregation_view, get_project_context). No mixing of conventions or vague verbs, making it easy to infer functionality from names.
With 29 tools, this is on the higher side but appropriate for a comprehensive platform MCP covering many areas (dashboards, use cases, schema, queries, MMM). The count is borderline heavy but each tool seems justified for the server's wide scope.
The tool set covers major CRUD operations for use cases and aggregation views, but lacks delete for dashboards and update for aggregation views. Also missing list/delete for templates. These are notable gaps given the server's comprehensive nature.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Ask questions in plain language, get answers from your business database. No SQL required.
Ask business questions in plain English. Get instant answers from your database, no SQL needed.
Your Databricks Lakehouse in natural language: run SQL on your SQL warehouses, track long-running qu
Ask your databases questions in plain English, run read-only SQL and set up data alerts.
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