
metabase-react-sdk-setup
First-time setup for the Metabase React SDK — instance detection, API key, dashboard discovery, JWT auth, SDK installation, and initial embedding code.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/metabase/agent-skills --skill metabase-react-sdk-setup- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads metabase-react-sdk-setup automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Use this skill for any task involving @metabase/embedding-sdk-react — whether that's initial setup, embedding dashboards, theming, or plugins.
Communication style: Be concise. Do one step at a time. When asking the user for input, output only the question — do not explain upcoming steps, implementation details, or what you plan to do next. The user does not need a roadmap.
CRITICAL — YOU MUST GET AN API KEY BEFORE DOING ANYTHING ELSE
Step 1 asks the user for a Metabase URL and API key. You CANNOT proceed without both. Do NOT detect the Metabase version, fetch
llms.txt, install packages, or write ANY code until the user has given you an API key. Do NOT attempt to call any Metabase API endpoint without an API key — it will return 401 and you will be guessing. If any Metabase API call returns 401, STOP everything and ask the user for an API key.
Step 1 — Get the Metabase URL and API key
You need a Metabase instance URL and an admin API key before anything else.
.env.metabase is only for admin tasks within this skill (API calls to Metabase). It is NOT the app's runtime config. Never import, read, or reference .env.metabase from the user's application code or build config. The app's instance URL goes in the user's own .env file (e.g., VITE_METABASE_URL, NEXT_PUBLIC_METABASE_URL) — set that up in Step 4.
Check if .env.metabase exists in the project root and already has both METABASE_INSTANCE_URL (non-empty) and METABASE_ADMIN_API_KEY (non-empty). If so, skip to Step 2.
Otherwise, create the file and gitignore it:
grep -qxF '.env.metabase' .gitignore 2>/dev/null || echo '.env.metabase' >> .gitignore
printf 'METABASE_INSTANCE_URL=\nMETABASE_ADMIN_API_KEY=\n' > .env.metabase
Then output only this message — no preamble, no explanation of what comes next, no implementation details:
I created
.env.metabasein the project root. Please fill in both values:
- Set
METABASE_INSTANCE_URLto your Metabase URL (e.g.http://localhost:3000)- Open
{your URL}/admin/settings/authentication/api-keys, create a new API key- Set
METABASE_ADMIN_API_KEYto that key- Let me know when you're done
Do not guess or assume the instance URL. Do not pre-fill localhost:3000. Do not ask the user to paste the key in the chat — it should only go in .env.metabase. Wait for the user to confirm, then proceed to Step 2.
Step 2 — Detect version and discover dashboards
Now that you have an API key, detect the version and find dashboards.
2a — Detect version
source .env.metabase && \
curl -s "$METABASE_INSTANCE_URL/api/session/properties" \
-H "X-API-Key: $METABASE_ADMIN_API_KEY" | grep -o '"tag":"[^"]*"'
Parse both the edition and the major version from the tag:
| Tag format | Edition | Example |
|---|---|---|
v0.X.Y | OSS (Community) | v0.60.1 → major 60, OSS |
v1.X.Y | Enterprise (EE) | v1.60.1 → major 60, EE |
If major version < 49, tell the user the Embedding SDK requires Metabase 49+ and stop.
If the tag starts with v1., the instance is Enterprise Edition — use full JWT SSO embedding. Do not fall back to guest embedding or any OSS-only auth path.
Remember the major version number — you will need it in Step 3.
2b — Enable the Embedding SDK
Automatically enable the SDK so the user doesn't have to toggle it manually in the admin panel:
source .env.metabase && \
curl -s -X PUT "$METABASE_INSTANCE_URL/api/setting/enable-embedding-sdk" \
-H "X-API-Key: $METABASE_ADMIN_API_KEY" \
-H "Content-Type: application/json" \
-d '{"value": true}'
If this returns an error (e.g., 403), tell the user to enable it manually at <INSTANCE_URL>/admin/settings/embedding and move on.
Do NOT fetch llms.txt yet. You need dashboard IDs first.
2c — Find dashboards and table candidates
Run both of these:
source .env.metabase && \
curl -s "$METABASE_INSTANCE_URL/api/search?models=dashboard&archived=false" \
-H "X-API-Key: $METABASE_ADMIN_API_KEY"
source .env.metabase && \
curl -s "$METABASE_INSTANCE_URL/api/automagic-dashboards/database/1/candidates" \
-H "X-API-Key: $METABASE_ADMIN_API_KEY"
Filter and prioritize the results:
- Exclude any dashboards from the "Usage analytics" collection — those are internal Metabase admin dashboards, not user content.
- Deprioritize anything from the "Sample Database" — prefer the user's own databases and dashboards.
- Pick the top 5 most relevant to what the user asked for from each category. Do not dump every result.
Format like this:
Existing dashboards:
- Sales Overview (ID 3)
- Customer Analysis (ID 7) ...
Or I can create a new dashboard from your data: A. Orders table B. Products table ...
Which ones should I embed? (e.g. "1 and 3" or "A")
Wait for the user to pick. If they choose a table, generate and save the X-ray dashboard:
source .env.metabase && \
DASHBOARD=$(curl -s "$METABASE_INSTANCE_URL/api/automagic-dashboards/table/<TABLE_ID>" \
-H "X-API-Key: $METABASE_ADMIN_API_KEY")
source .env.metabase && \
curl -s "$METABASE_INSTANCE_URL/api/dashboard/save" \
-H "X-API-Key: $METABASE_ADMIN_API_KEY" \
-H "Content-Type: application/json" \
-d "$DASHBOARD"
The save response contains the persisted dashboard with a real id field. Use these IDs going forward.
Step 3 — Fetch docs, set up auth, and install SDK
You MUST have real dashboard IDs before reaching this step. If you don't, go back to Step 2.
Now fetch the versioned docs index using the major version from Step 2a:
curl -s https://www.metabase.com/docs/v0.<MAJOR>/llms.txt
Fall back to https://www.metabase.com/docs/latest/llms.txt if empty. This contains correct prop names, auth config shapes, SDK install commands, and breaking changes for this version. Do not fetch llms-embedding-full.txt (too large).
3a — Set up JWT SSO authentication (skip if already done)
Follow the auth setup instructions in llms.txt. In particular:
- Retrieve the JWT signing secret from Metabase: Settings → Admin → Embedding → Embedding secret key
- Tell the user to save it as
METABASE_JWT_SECRETin their server-side environment only (never a browser-accessible env var) - Ask which backend framework they are using (Next.js API route, Express, Fastify, etc.) and scaffold a minimal JWT signing endpoint following the pattern in
llms.txt
3b — Install the SDK (skip if already installed at correct version)
Check whether @metabase/embedding-sdk-react is already in the user's package.json.
- If not installed: use the install command from
llms.txt(the correct dist-tag matches the instance major version). - If already installed: verify the major version matches. Warn on mismatch and offer to update.
Step 4 — Generate embedding code
Use llms.txt as the authoritative reference for all API shapes. Write files directly into the user's project — edit existing files in place rather than creating new ones alongside them.
Code conventions (override anything in the docs)
- JWT SSO only: API keys grant admin-level access and are not safe for end-user embeds. Use a server-side JWT signing endpoint;
MetabaseProviderreceives its URL. Never generateapiKey,METABASE_API_KEY,api-key, orx-api-key— not even as a placeholder. Deviate only if the user explicitly asks and acknowledges the security risk. - Instance URL from env:
VITE_METABASE_URL(Vite),NEXT_PUBLIC_METABASE_URL(Next.js), etc. Never hardcode. - Dashboard IDs as inline literals: always hardcode dashboard IDs directly in JSX — e.g.
<InteractiveDashboard dashboardId={7} />. Dashboard IDs are not secrets. Never useimport.meta.env.VITE_METABASE_DASHBOARD_*, env vars, config objects,parseDashboardIdhelpers, or any indirection for dashboard IDs. The goal is clean, minimal code the user can instantly understand and tweak. - Secrets server-side only: JWT secrets must never appear in browser-accessible env vars or frontend code.
Theming
After generating the embedding code, inspect the user's app for existing styles — look at CSS variables, Tailwind config, or theme files. Set the theme prop on MetabaseProvider to match the app's look and feel. At minimum, align:
colors.brand— the app's primary/accent colorcolors.background— to match the page background so the embed doesn't look like a white box on a dark page (or vice versa)fontFamily— to match the app's font
Refer to llms.txt for the full theme shape. Keep it minimal — only set values that differ from Metabase defaults.
FAQ
What does the metabase-react-sdk-setup skill do?
First-time setup for the Metabase React SDK — instance detection, API key, dashboard discovery, JWT auth, SDK installation, and initial embedding code.
How do I install metabase-react-sdk-setup?
Run npx skills add https://github.com/metabase/agent-skills --skill metabase-react-sdk-setup in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/metabase-react-sdk-setup/ (personal) or .claude/skills/metabase-react-sdk-setup/ (project).
Which AI agents can use metabase-react-sdk-setup?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is metabase-react-sdk-setup safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains metabase-react-sdk-setup?
It is published by metabase in metabase/agent-skills. It has 365 recorded installs.
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