| title | AI agent resources for embedding |
|---|---|
| summary | Agent skills and llms.txt to help AI coding agents embed Metabase in your app. |
If you use an AI coding agent, you can give the agent Metabase-specific context to help with embedding setup, upgrades, and migrations.
We've developed some agent skills to give your AI agents step-by-step playbooks for specific embedding tasks.
| Skill | Description |
|---|---|
| SDK version upgrade | Upgrade your modular embedding SDK, including changelog checks and breaking change handling. |
| Full app → modular embedding | Migrate from full app embedding to modular embedding. |
| Modular embedding → SDK (React) | Migrate from script-based modular embedding to the React SDK. |
| Static → guest embeds | Migrate from static (signed) embeds to guest embeds. |
| SSO for embeds | Set up SSO authentication for embedded Metabase. |
Browse all skills on the agent skills repo.
Agents can read the docs you're reading now (and many agents have already read our docs), but we also publish llms.txts so that you can give your AI agent:
If you're on a specific version (e.g., v0.58), you can use versioned llms.txt files scoped to that version's docs:
https://www.metabase.com/docs/v0.58/llms.txthttps://www.metabase.com/docs/v0.58/llms-embedding-full.txt
Always review and validate the changes made by agents. Check that your application builds, tests pass, and the embedding works as expected before committing anything.