Validate compact backend specs and generate tested NestJS, Prisma, and PostgreSQL repositories.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
BackendGen is a deterministic backend compiler for AI coding agents. Give an agent a compact, versioned YAML or JSON specification and it can generate a structured, tested backend instead of inventing database models, permissions, API routes, and migrations from scratch.
It currently generates NestJS 11 + Prisma 6 + PostgreSQL repositories,
including a typed TypeScript client and a small frontend-contract.json for
the frontend agent to consume. Generated projects have no BackendGen runtime
dependency.
Alpha status: BackendGen is ready for design-partner trials and local projects. Review generated applications before production use; it has not yet completed independent security review or three design-partner trials.
npm CLI Β· npm MCP server Β· Report an issue Β· Design-partner program
BackendGen is useful when an AI agent needs a real backend behind a frontend:
BackendGen is not a hosted backend service, deployment platform, or frontend builder. It runs locally and produces code that a developer or coding agent can review, customize, test, deploy, and connect to a frontend.
You do not need an npm account or this repository to try BackendGen.
The generated project runs prisma generate during installation, so this
first-run path does not require a separate Prisma command. From the parent
directory, use
npx -y @2hemi/backendgen test-generated --output ./team-api --install when an
agent should perform installation, validation, build, and unit tests through
one bounded compiler command.
init creates a valid starter specification. Edit backend.yaml, then run
validate and generate again. Before regenerating an existing project, use
diff to preview what would change:
The repository includes working specifications from basic CRUD to a full-featured backend. This multi-tenant task example is a good first test:
Browse every example and what it demonstrates in examples/README.md:
| Example | Demonstrates |
|---|---|
| notes API | CRUD, filtering, pagination, and sorting |
| auth notes | Accounts, roles, ownership, and authentication |
| SaaS tasks | Organizations and enforced tenant isolation |
| hotel booking | Reservations, overlap prevention, and notifications |
| all features | CRUD, auth, organizations, reservations, notifications, webhooks, jobs, and uploads |
The MCP package lets an AI agent discover supported backend features, validate a spec, preview changes, generate a backend, run generated tests, return the frontend handoff contract and customization guidance. It can also explain customization points. It runs locally over stdioβno BackendGen account or network listener is required.
Migration SQL is returned only when the agent explicitly requests it for review; generated source remains omitted from normal responses.
Add this server to an MCP-capable client, giving it only a directory you trust:
For Codex, Claude Code, Cursor, ChatGPT desktop, Windows, Lovable Desktop, and the correct v0 handoff, follow the client-specific commands in docs/AI_BUILDERS.md. The complete MCP security and tool reference is in docs/MCP.md.
Once connected, give your agent a request such as:
Create a multi-tenant task-management backend. First inspect BackendGen's capabilities and relevant features. Write a spec, validate it, preview the generation, generate it inside this project, and run the generated tests. Keep custom behavior in the documented customization points.
For a valid specification, BackendGen produces a standalone repository with:
src/generated/ for compiler-owned code and src/custom/ for code you own;.backendgen/manifest.json that records ownership and hashes;frontend-contract.json and a typed TypeScript client for frontend agents.On regeneration, BackendGen preserves custom files, refuses to overwrite edited
generated files unless you explicitly use --force, and requires explicit
review for destructive or data-dependent schema changes. Read
docs/MIGRATIONS.md before changing a live schema.
The repository's CI verifies compiler, CLI, MCP, security-contract fuzzing, package-installation, and generated-project scenarios. Generated projects are also built and tested against PostgreSQL in the release test matrix. See the local verification record and security contract for the exact evidence.
That evidence does not prove that every generated application is safe for production. You remain responsible for reviewing the specification, generated code, secrets, infrastructure, and deployment configuration.
Current boundaries:
| If you need to⦠| Read |
|---|---|
| Write a specification | Specification reference |
| Understand each supported feature | Feature packs |
| Connect an AI agent or MCP client | AI builder integration |
| Customize a generated project | Customization guide |
| Safely regenerate or change a schema | Migrations guide |
| Run tests locally | Local testing |
| Understand security boundaries | Threat model |
| Contribute | Contributing |
We are looking for developers and AI builders who will test BackendGen on a real, non-production project. Please open an issue with:
backend.yaml specification;Never include API keys, .env files, private customer code, or production
database data. For security vulnerabilities, follow SECURITY.md
instead of opening a public issue. Full support details are in SUPPORT.md.
To work on BackendGen itself:
Maintainers preparing a release can run the same non-publishing gate through
npm run verify:release. PostgreSQL-backed execution remains the separate
npm run verify:local:postgres workflow described in
local testing.
BackendGen is licensed under Apache-2.0. Generated projects belong to their users.
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