--- title: Introduction description: How KTX gives analytics agents trusted context for warehouse work. ---

Make analytics context{'\n'}usable by agents

KTX turns warehouse metadata, semantic definitions, and business knowledge into reviewable project files that agents can use while planning, querying, and updating analytics work.

Get Started The Context Layer Building Context
## Who KTX is for KTX is built for analytics engineers and data teams who want data agents to work on real analytics systems - not just generate one-off SQL. Use KTX when you want agents to: - **Generate SQL** from approved measures and joins - **Repair semantic definitions** through reviewable diffs - **Explain metric provenance** with warehouse evidence - **Work alongside** dbt, LookML, MetricFlow, Looker, Metabase, and modern BI platforms Works with PostgreSQL, Snowflake, BigQuery, ClickHouse, MySQL, and SQL Server. ## Explore the docs Set up KTX and build your first context in under 10 minutes. Understand what a context layer is and why agents need one. Hands-on workflows for scanning, ingesting, writing, and serving. Complete flag and subcommand reference for every KTX command. ## Agent usage notes | Agent task | Read next | |------------|-----------| | Discover machine-readable docs | [AI Resources](/docs/ai-resources) | | Learn how a coding assistant should approach KTX | [Agent Quickstart](/docs/ai-resources/agent-quickstart) | | Set up a new KTX project | [Quickstart](/docs/getting-started/quickstart) | | Explain what problem KTX solves | [The Context Layer](/docs/concepts/the-context-layer) | | Scan a database and ingest metadata | [Building Context](/docs/guides/building-context) | | Edit semantic sources or wiki pages | [Writing Context](/docs/guides/writing-context) | | Look up exact command flags | [CLI Reference](/docs/cli-reference/ktx-setup) |