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ktx (GitHub Repo)
Kaelio's open-source `ktx` provides a local, self-improving context layer for data agents like Claude, Codex, and Cursor to generate accurate SQL from trusted metric definitions and company knowledge.
What: `ktx` is a local context layer that helps data agents query warehouses by combining approved metrics, join logic, warehouse metadata, and company knowledge. It works with PostgreSQL, Snowflake, BigQuery, ClickHouse, MySQL, SQL Server, and SQLite, and integrates with dbt, MetricFlow, LookML, Looker, Metabase, and Notion. It runs locally and doesn't send schema or query results to a hosted service.
Why it matters: This tool addresses the critical challenge of ensuring AI agents produce accurate, trustworthy results in complex data environments, highlighting the need for specialized context management layers beyond general-purpose LLMs or traditional semantic layers. It points to a future where agents require meticulously curated and integrated knowledge bases to be truly effective in enterprise data analytics.
Takeaway: If you use data agents like Claude Code or Cursor with a SQL warehouse and struggle with consistent, accurate queries, explore `ktx` as a local, open-source context layer to improve reliability.
Decoder
- Data agent: An AI system designed to perform tasks involving data, often by interacting with databases, APIs, or other data sources.
- Semantic layer: A layer in a data architecture that translates complex database structures into business-friendly terms, providing a consistent view of data for reporting and analysis.
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