Spala
Use case

Backend for AI-Built Apps

Use Spala when an AI-built frontend needs a real backend contract with database, auth, APIs, validation, docs, publishing, and MCP handoff.

Create Account Start Guide Public MCP
DescribeUse Copilot and Lite Mode to shape backend intent.
InspectReview tables, endpoints, auth, logic, and settings.
TestUse API Playground and generated docs before handoff.
PublishShip an API your frontend or approved agent can use.

When this is a fit

Founders and teams who used AI to build screens or an MVP and now need the backend to be inspectable and maintainable.

Database Model

Tables, relationships, field types, ownership boundaries, and the records the frontend should expect.

Auth And Role Rules

Signup/login routes, session or token behavior, protected endpoints, roles, and access checks.

REST API Contract

Route paths, methods, request bodies, response shapes, status codes, and route-specific errors.

Validation

Required fields, allowed values, ownership checks, failure behavior, and examples the frontend can handle.

Generated Docs

OpenAPI, Markdown, or SDK-style references a developer or coding agent can use without guessing.

Frontend Handoff Packet

API base URL, auth routes, CORS origins, docs, upload/realtime notes, errors, and publish state.

MCP Project Handoff

Public MCP discovery, OAuth, project selection, and the exact project MCP URL returned by Spala.

Recommended workflow

  1. Describe the backend outcome to Spala AI Copilot.
  2. Inspect the generated project graph and resource list.
  3. Test endpoints, auth, validation, and CORS.
  4. Share the generated API docs and frontend handoff packet.
  5. Use public MCP for agent discovery and authenticated project MCP for scoped backend work.

Evaluation boundary

Spala should be validated with a small proof-of-concept before serious production use. Verify data export, backups, compliance requirements, project permissions, secrets, and support needs directly.