ktx

The context layer for data agents

Quickstart · CLI Reference · Agent Setup · Slack

Built and maintained by Kaelio

---

ktx is a self-improving context layer that teaches agents how to query your warehouse accurately - from approved metric definitions, joinable columns, and business knowledge it builds and maintains for you.

[!NOTE] Run ktx with your own LLM API keys or a local agent sign-in — a Claude Pro/Max subscription through Claude Code, or your local Codex authentication. No extra usage billing from ktx.

Why ktx

General-purpose agents struggle on data tasks. They re-explore your warehouse on every question, invent their own metric logic, and return numbers that don't match approved definitions.

Traditional semantic layers don't fix this. They demand constant manual upkeep and don't absorb the rest of your company's knowledge.

ktx does both, automatically:

• Learns from company knowledge. Ingests wiki content, organizes it, removes duplicates, and flags contradictions for human review.
• Maps the data stack. Samples tables, captures metadata and usage patterns, detects joinable columns, and annotates sources so agents write better queries.
• Builds a semantic layer. Combines raw tables and high-level metrics through a join graph that automatically resolves chasm and fan traps, so agents fetch metrics declaratively instead of rewriting canonical SQL each time.
• Serves agents at execution. Exposes CLI and MCP tools with combined full-text and semantic search across wiki and semantic-layer entities.

How ktx compares

	General-purpose agent	Traditional semantic layer	ktx
Builds warehouse context automatically	—	—	✓
Detects joinable columns + resolves fan/chasm traps	—	Manual	✓
Approved, reusable metric definitions	—	✓	✓
Absorbs wiki / Notion / team knowledge	—	—	✓
Flags contradictions across sources	—	—	✓
Ships CLI + MCP for agent execution	Partial	—	✓
Read-only by design	n/a	n/a	✓

Who is ktx for

Use ktx if you:

• Want agents like Claude Code, Codex, Cursor, or OpenCode to query your warehouse with approved metric definitions
• Have business knowledge scattered across dbt, Looker, Metabase, Notion, and team wikis
• Need agents to reuse canonical SQL instead of inventing it on every prompt

Skip ktx if you:

• You don't have a SQL warehouse - ktx sits on top of one
• You only need one ad-hoc query - psql or a notebook will do

Works with PostgreSQL, Snowflake, BigQuery, ClickHouse, MySQL, SQL Server, SQLite, DuckDB, Amazon Athena, and MongoDB. Integrates with dbt, MetricFlow, LookML, Looker, Metabase, Sigma, Notion, and Google Drive.

Quick Start

npm install -g @kaelio/ktx
ktx setup
ktx status

ktx setup creates or resumes a local ktx project, configures providers and connections, builds context, and installs agent integration.

Example ktx status after setup:

ktx project: /home/user/analytics
Project ready: yes
LLM ready: yes (claude-sonnet-4-6)
Embeddings ready: yes (text-embedding-3-small)
Databases configured: yes (warehouse)
Context sources configured: yes (dbt_main)
ktx context built: yes
Agent integration ready: yes (codex:project)