ktx
Allows querying ClickHouse databases as data sources for the context layer.
Ingests dbt semantic layers to combine with raw-table introspection and wiki content.
Supports Google Vertex AI as an LLM backend for context generation.
Integrates with Looker (LookML) to import metric definitions and dimensions.
Integrates with Metabase to capture business logic and usage patterns.
Allows querying MySQL databases as data sources.
Ingests wiki content from Notion for business context.
Allows querying PostgreSQL databases as data sources.
Allows querying Snowflake databases as data sources.
Allows querying SQLite databases as data sources.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ktxShow approved metrics for monthly revenue"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
Runktx with your own LLM API keys or a Claude Pro/Max subscription. 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 -
psqlor a notebook will do
Works with PostgreSQL, Snowflake, BigQuery, ClickHouse, MySQL, SQL Server, and SQLite. Integrates with dbt, MetricFlow, LookML, Looker, Metabase, and Notion.
Quick Start
npm install -g @kaelio/ktx
ktx setup
ktx statusktx 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)Already using an agent? Ask Claude Code, Codex, Cursor, or OpenCode from your project directory:
Follow instructions from
https://docs.kaelio.com/ktx/docs/agents-setup.md
to install and configure ktxIfktx status prints ktx mcp start --project-dir ..., run it before
opening your agent client.
First commands
Command | Purpose |
| Create, resume, or update a ktx project |
| Check project readiness |
| Build context for every configured connection |
| Search semantic sources |
| Search local wiki pages |
| Start the MCP server for agent clients |
See the CLI Reference for every command, flag, and option.
Project Layout
my-project/
├── ktx.yaml # Project configuration
├── semantic-layer/<connection-id>/ # YAML semantic sources
├── wiki/global/ # Shared business context
├── wiki/user/<user-id>/ # User-scoped notes
├── raw-sources/<connection-id>/ # Ingest artifacts and reports
└── .ktx/ # Local state and secrets, git-ignoredCommit ktx.yaml, semantic-layer/, and wiki/. Keep .ktx/ local.
Project resolution defaults to KTX_PROJECT_DIR, then the nearest ktx.yaml,
then the current directory. Pass --project-dir <path> when scripting.
FAQ
Does ktx send my schema or query results to a hosted service? No. ktx runs locally. The only data leaving your machine is what you send to the LLM provider you configured.
Which LLM backends are supported? Anthropic API, Google Vertex AI, AI Gateway, and the local Claude Code session through the Claude Agent SDK. See LLM configuration.
How is ktx different from a dbt or MetricFlow semantic layer? ktx ingests those layers and combines them with raw-table introspection and wiki content. Agents get one searchable surface instead of three disconnected ones - and ktx flags contradictions across sources.
Does ktx need a running server? There is no hosted service. The local MCP daemon runs on demand via
ktx mcp startwhen an agent client needs it.Is my warehouse safe? Yes. Connections are read-only - ktx never writes to your database.
Docs
Community
Slack — ask questions, share what you're building, and chat with maintainers.
GitHub Issues — report bugs and request features.
Contributing — set up the repo, run tests, and open a PR.
Development
git clone https://github.com/kaelio/ktx.git
cd ktx
pnpm install
uv sync --all-groups
pnpm run build
pnpm run checkktx is a pnpm + uv workspace:
Path | Purpose |
| TypeScript CLI and published npm package source |
| Core context engine |
| LLM and embedding providers |
| Database scan connectors |
| Semantic-layer query planning |
| Portable compute service |
Local development CLI:
pnpm run setup:dev
pnpm run link:dev
ktx-dev --helpUseful checks:
pnpm run type-check
pnpm run test
pnpm run dead-code
uv run pytest -qTelemetry
ktx collects anonymous usage telemetry from interactive CLI runs to improve setup, command reliability, and data-agent workflows. No file paths, hostnames, SQL, schema names, error messages, or argv are recorded. See Telemetry for the event catalog and opt-out options.
License
ktx is licensed under the Apache License, Version 2.0. See LICENSE.
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