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The AI Collection Creator is an in-dashboard agent that turns a natural-language description of your app into a set of production-ready MongoDB collections. You describe what you’re building, iterate on the schema through chat, review the design on an interactive canvas, and create every collection in your project with a single click. Use it when you want to bootstrap a new project’s data model quickly instead of clicking through the manual field builder one collection at a time.

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When to use it

  • New project bootstrap — turn a product idea (“multi-tenant SaaS with workspaces, projects, and tasks”) into 5–15 collections without hand-designing each one.
  • Exploring a schema shape — iterate on relationships and field types in chat before committing anything to the database.
  • Reference designs — ask for well-known patterns (e-commerce, CMS, subscription billing) as a starting point you can then edit manually.
If you already know the exact shape of a single collection, the manual builder is faster. See Collections & Schemas for the manual flow and field-type rules.

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Open the AI Collection Creator

  1. In the dashboard, open your project.
  2. Go to Database and click Create Collection.
  3. At the top of the create-collection page, switch the mode selector from Manual Builder to AI-Assisted.
The page splits into two panels:
  • Left — AI Schema Assistant. A chat with the agent, plus a model selector and quick-start prompts.
  • Right — Schema Canvas. An interactive visualizer that renders the proposed schema as connected cards, one per collection. Fields, types, required/unique flags, and Ref relationships are drawn as edges between cards.

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Chat with the agent

Type a description of your app into the composer and press Enter (or Shift+Enter for a newline). The agent responds with either:
  • A clarifying question, if it needs more detail before designing a schema.
  • A proposed set of collections, which appear as cards on the Schema Canvas on the right.
You can keep chatting to refine the design — add fields, split a collection, change a type, add references, remove something you don’t need. Each turn updates the Schema Canvas in place.

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Quick-start prompts

When the chat is empty, the assistant offers a few one-click prompts you can send as-is or edit. They currently cover:
  • E-commerce Platform — products, categories, orders, customers, product reviews.
  • Project Management SaaS — workspaces, projects, tasks, milestones, team members.
  • Subscription Billing API — plans, subscriptions, invoices, payment methods, usage logs.
  • Content Management (CMS) — articles, authors, categories, media assets, publishing revisions.
Use these as starting points, then iterate in chat.

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Model selector

A dropdown at the top of the chat panel lets you pick the model used for the next turn. The default (qwen/qwen3.6-27b) and openai/gpt-oss-120b currently produce the best schema designs; smaller models are faster but may return simpler results. Individual messages are limited to 2,000 characters. Longer inputs return a 400 error asking you to shorten the message.

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Review the schema on the Schema Canvas

Every proposed collection is rendered as a card on the canvas on the right:
  • Each row is one field with its type.
  • Required and unique flags are marked on the field.
  • Ref fields draw an edge to the referenced collection so you can see relationships at a glance.
  • Object and Array fields show their nested shape.
You can pan and zoom the canvas to inspect large designs. The canvas updates whenever the agent returns a new schema in chat.

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Create the collections

When you’re happy with the design, click Insert All above the Schema Canvas. urBackend asks you to confirm, then creates every collection in the design in a single bulk operation. When the call finishes:
  • Each collection is either marked as created or listed with the reason it failed (for example, a name that already exists in the project).
  • A toast summarizes how many collections were created and how many failed.
  • The chat session is cleared so you can start a fresh design.

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Bulk creation limits

The bulk-create endpoint enforces the following:
  • Maximum 20 collections per Insert All call. Designs larger than 20 collections must be split across multiple sessions.
  • Your project’s overall collection limit (from your plan) still applies. If Insert All would exceed it, the excess collections fail with Collection limit reached.
  • Duplicate names against collections that already exist in the project fail with Collection already exists. Other collections in the same batch still succeed.

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The users collection is reserved

The AI Collection Creator never creates a collection named users. It’s stripped from the AI response before the schema reaches the canvas, and the bulk-create endpoint additionally rejects any collection named users with a 403. The users collection has a fixed schema contract used by the auth system. Create it manually from the Manual Builder tab, where the dashboard pre-fills the required email and password fields. See Collections & Schemas — The users collection and the Authentication guide.

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Session iteration limits

A single AI Collection Creator session is capped at 20 iterations (user + assistant turn pairs) when using the urBackend platform key. When you approach the limit, the composer shows a counter (N of 20 AI turns used). When you hit it, the composer is disabled and the next request returns:
Chat transcripts are cached for 2 hours. Clicking Reset chat in the canvas panel clears the transcript, resets the iteration counter, and starts a fresh session.

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BYOK bypasses the iteration cap

If you’ve configured a personal Groq API key at the developer or project level, the iteration cap does not apply — you can iterate as many turns as you like in a single session, subject only to Groq’s own rate limits and billing on your key. BYOK also removes the platform-key monthly AI session cap that applies to other AI features. See BYOK for AI for how to configure a key.

Related topics

BYOK for AIAugust 2026Collections & SchemasLimits & Quotas