Motherduck Rest Api logo

Motherduck Rest Api

Organization
motherduckdb
motherduck-rest-api

Administer MotherDuck service accounts, tokens, Ducklings, and Dive embed sessions through the control-plane REST API.

Overview

Publishermotherduckdb
Repositoryagent-skills
Skill namemotherduck-rest-api
Stars
62
Forks
6
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by motherduckdb on GitHub. Read the source before you install it.

Installation

Install the Motherduck Rest Api AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/motherduckdb/agent-skills/tree/main/plugins/motherduck-skills-claude/skills/motherduck-rest-api
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/motherduckdb/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/plugins/motherduck-skills-claude/skills/motherduck-rest-api .claude/skills/motherduck-rest-api
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Motherduck Rest Api in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Motherduck Rest Api on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Motherduck Rest Api is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

REST API Administration

Source Of Truth

  • Prefer current MotherDuck REST API documentation, the public OpenAPI spec at https://api.motherduck.com/docs/specs, or an explicit OpenAPI spec supplied by the user.
  • For token scope and embed behavior, cross-check the REST API docs and the Embedded Dives docs because they include operational constraints not obvious from the raw schema.
  • If the MotherDuck MCP ask_docs_question feature is available, use it to check whether public REST API guidance has changed.
  • Treat endpoint availability, preview status, token fields, and role requirements as current only when backed by the supplied spec or current docs.

Default Posture

  • Treat the REST API as the control plane; SQL and data-plane queries go through a database connection, not the REST API.
  • Use https://api.motherduck.com as the base URL unless the user provides another environment.
  • Authenticate with Authorization: Bearer ${MOTHERDUCK_ADMIN_TOKEN} and keep admin read-write tokens in backend-managed secrets.
  • Never use read-scaling tokens for REST API administration.
  • Prefer read-before-write flows for configuration changes so the current account, service account, Duckling config, or Dive metadata is known before mutation.
  • Treat POST /v1/users as service-account creation unless current docs explicitly broaden the API. GET /v1/users lists every user and service account in the org; filter with is_service_account and is_deprovisioned and page with limit/offset. Use it for access reviews and to find a service account before creating a duplicate.
  • Service accounts and access tokens accept an optional, searchable description. Set one that names the workload and owner; check the current API spec for the field name.
  • For the Terraform resources, state rules, and setup archetypes, read references/ACCESS_CONTROL_SETUPS.md in motherduck-security-governance.
  • For repeatable provisioning (environments, partner or per-customer setups), prefer the Terraform provider motherduckdb/motherduck over scripted REST calls. It authenticates with MOTHERDUCK_TOKEN, plus MOTHERDUCK_ADMIN_TOKEN for service accounts, tokens, and Duckling configuration.
  • Assume active-account, Duckling configuration, service-account creation, service-account token creation, and Dive embed-session endpoints require an organization admin bearer token unless current docs say otherwise.
  • Never expose generated access tokens in logs, browser code, client bundles, or committed files.
  • Confirm destructive deletes with the user. Deleting a user permanently deletes that user and all of their data.
  • Treat agent/account signup (motherduck new or the public signup flow) as separate from the organization Admin REST API. Never create an account because an admin token is unavailable.
  • For Dive embed sessions, keep initial_state JSON-serializable and within the documented size limits; validate iframe state, navigation, and export messages in the host application.

Workflow

  1. Identify whether the task is service-account provisioning, token management, Duckling sizing, active-account inspection, or Dive embedding.
  2. Resolve the admin token from the existing environment and identify the target username or dive_id; ask only when a required value cannot be discovered, and never invent production identifiers.
  3. Check token scope before calling token endpoints: users can create tokens for themselves, and admins can create tokens for service accounts, but admins cannot create tokens for other non-service-account members through the API.
  4. For Duckling config changes, read the current config first, then update both read_write and read_scaling because the PUT payload requires both.
  5. Preserve response fields that are only returned once, especially newly created token strings and embed session strings.
  6. Surface API errors by status and response body; do not hide 400, 401, 403, 404, or 500 responses behind success-shaped fallbacks.
  7. If the connected MotherDuck MCP server lists user-admin tools (such as create_service_account), prefer them over raw HTTP and call get_user_admin_guide first when it is listed. Many MCP setups do not expose them; then use the REST API directly. The MCP column in references/REST_API_GUIDE.md maps the names.

For answer, review, or planning requests, inspect and report without mutating the control plane. For create or update requests, perform the requested in-scope operation and verify the response; retain confirmation for destructive deletes or broader administrative changes.

References

Read only the reference sections needed for the current task.

  • Read references/REST_API_GUIDE.md for endpoint summaries, MCP tool mapping, curl examples, validation limits, and operational gotchas.

Related Skills

Load related skills only for missing capabilities; reuse established context.

  • motherduck-query for SQL and data-plane query work
  • motherduck-connect for connection tokens and application connection posture
  • motherduck-security-governance for admin-token handling, service-account posture, and access-boundary questions
  • motherduck-create-dive for designing Dives before minting embed sessions

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Motherduck Rest Api AI skill do?

Administer MotherDuck service accounts, tokens, Ducklings, and Dive embed sessions through the control-plane REST API.

Why use Motherduck Rest Api on TypingMind?

Because you install it once and use it with any model. Motherduck Rest Api is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Motherduck Rest Api in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/motherduckdb/agent-skills/tree/main/plugins/motherduck-skills-claude/skills/motherduck-rest-api. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Motherduck Rest Api?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Motherduck Rest Api?

As many as you like. As long as a model supports skills, you can use Motherduck Rest Api with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Motherduck Rest Api AI skill free?

Yes. It is published on GitHub by motherduckdb under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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