Everything runs on your machine — your file is processed right here in your browser and never uploaded to any server.
Input
JSON
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Output
Mongoose schema
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About this tool

When you build a Node.js application on MongoDB, every collection needs a Mongoose schema — and writing one field by field from an existing document is slow, repetitive work. This tool inspects a sample JSON document and generates the matching Mongoose schema definition automatically, with a field entry for every key.

It shines when you inherit an existing database and need models for collections you did not design: export one representative document, paste it here, and scaffold the schema in seconds. It is equally useful in API-first development, where an agreed-upon JSON payload becomes the blueprint for your data layer.

How to use

  1. Paste a representative JSON document into the left editor, or select one from your machine using Load File.
  2. The generated Mongoose schema code appears in the right editor at once and tracks every edit you make.
  3. Read through the inferred field types and rename anything that should not follow the sample exactly.
  4. Copy the schema into your models directory with the Copy button, or save it via Download.

Schema generation runs entirely on your side of the screen. The sample documents you paste are analyzed by local JavaScript in the browser tab and are never transmitted, so real user records can be used as samples without concern.

Frequently asked questions

How are field types determined?

Each value in your sample document is inspected and mapped to a Mongoose type such as String, Number, Boolean, or Date. Nested objects become embedded subdocument definitions and arrays become typed array fields.

Does the generated schema include validation rules?

No. The output defines field names and types only, since requirements like required, unique, or enum cannot be inferred from a single sample. Add those options by hand once the scaffold is in place.

Can I paste a deeply nested document?

Yes. Nested objects and arrays of objects are translated into nested schema structures, so complex documents with embedded subdocuments convert just as well as flat ones.