Aggregation And Grouping Query Generation

via “aggregate function support with group by and having clause execution”

Create, query, and analyze SQLite databases via MCP.

Unique: Executes aggregate queries through the same MCP tool interface as regular queries, with no special handling required. The server relies on SQLite's native aggregate engine, ensuring correct NULL handling and type coercion according to SQL semantics.

vs others: More flexible than pre-computed aggregates because it supports arbitrary GROUP BY and HAVING clauses; more efficient than post-query aggregation in the client because it leverages SQLite's optimized aggregate engine.

via “aggregation pipeline with grouping, reduction, and expression evaluation”

A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.

Unique: Implements a composable pipeline architecture where each stage (filter, group, reduce, sort, limit) is a pluggable result processor (src/result_processor.c), enabling complex aggregations without writing custom code; expression evaluation system (src/rlookup.h, RLookup) supports field references and mathematical operations evaluated during pipeline execution

vs others: Faster than running aggregations in application code because computation happens in-process within Redis; more flexible than SQL GROUP BY because pipeline stages can be dynamically composed and expressions are evaluated at query time

via “aggregation-and-grouping-query-generation”

via “aggregation-and-grouping-query-generation”

via “data-aggregation-and-grouping”

via “data-aggregation-and-summarization”

via “basic data aggregation and summarization”