How to define an enum in MSON?

Use the 'enum' structure type with nested items specifying different types, as shown in the 'Non-uniform Property' example where 'tag' can be a string or an object. This allows for flexible value definitions in your data structures.

MSON vs JSON Schema: which is better for API docs?

MSON is ideal for human-readable discussions and generating multiple formats from one source, while JSON Schema offers more comprehensive validation features. Choose MSON if readability and format-agnosticism are priorities, but use JSON Schema for advanced validation needs.

Can MSON generate XML schemas?

Yes, the README mentions that MSON is capable of producing XML representations, though the examples focus on JSON and JSON Schema. It's designed to be agnostic to common markup formats like XML and YAML.

What tools support MSON parsing?

MSON is integrated with Apiary's API Blueprint ecosystem, so tools like Apiary.io or the API Blueprint parser can handle it. However, standalone tooling may be limited compared to more established formats like JSON Schema.

Is MSON good for real-time data validation?

While MSON can derive JSON Schema for validation, it's primarily a description format, not a high-performance validation engine. For real-time validation, you might need to convert MSON to JSON Schema and use dedicated libraries.

How does MSON handle nested objects?

Nested objects are defined using Markdown lists with indentation, as shown in the 'Objects & Arrays' section where 'address' contains 'street', 'city', and 'state'. This mirrors natural Markdown nesting for clarity.

MSON — Markdown Syntax for JSON Description

What is MSON?

MSON (Markdown Syntax for Object Notation) is a plain-text format for describing data structures like JSON, JSON Schema, XML, or YAML in a human-readable way. It solves the problem of discussing and validating data structures by providing a common, markup-agnostic language that can be converted into various output formats. Originally developed as part of API Blueprint, it helps describe HTTP payloads and simplify content negotiation.

Target Audience

API designers, technical writers, and developers who need to document, validate, or negotiate data structures in APIs or other data-exchange scenarios. It's particularly useful for teams working with multiple representation formats.

Value Proposition

Developers choose MSON because it combines the simplicity of Markdown with the precision needed for data modeling, enabling clear communication about data structures without being tied to a specific serialization format. Its integration with API Blueprint makes it a powerful tool for API description and validation.

Markdown Syntax for Object Notation

Use Cases

Best For

Describing JSON or JSON Schema structures in plain text
Documenting API request/response payloads for team discussion
Creating reusable data type definitions for API specifications
Simplifying content negotiation in resource-based APIs
Generating multiple output formats (JSON, XML, YAML) from a single source
Validating data structures in API Blueprint projects

Not Ideal For

Projects requiring full JSON Schema validation with advanced keywords like uniqueItems or exclusiveMinimum
Teams working primarily with binary data or custom serialization formats not covered by basic types
Environments where direct YAML/JSON editing is preferred and a Markdown abstraction adds unnecessary overhead

Pros & Cons

Pros

Human-Readable Syntax

Uses familiar Markdown lists and headers to define data structures, making them easy to write and discuss in plain text, as shown in examples like the simple 'Product' object.

Multi-Format Generation

Can output JSON, JSON Schema, XML, or YAML from a single MSON description, facilitating markup-agnostic resource descriptions and content negotiation.

Reusable Type Definitions

Supports named types, references, and mixins for DRY data modeling, demonstrated in the 'Address' and 'User' examples with the 'Include' keyword.

Validation Integration

Enables validation of HTTP payloads through derived JSON Schema, making it a natural fit for API Blueprint projects and API documentation.

Cons

Limited JSON Schema Coverage

The README explicitly states it does not support all JSON Schema keywords, such as uniqueItems or exclusiveMinimum, restricting its use for complex validation scenarios.

Syntax Complexity for Edge Cases

Advanced features like multi-line descriptions require careful use of keywords like 'Properties' to avoid parsing conflicts, which can be error-prone and less intuitive.

Ecosystem Niche

Developed primarily for API Blueprint by Apiary, which may result in limited tooling and community support outside of API documentation contexts.

What is MSON?

Target Audience

Value Proposition

Use Cases

Best For

Describing JSON or JSON Schema structures in plain text
Documenting API request/response payloads for team discussion
Creating reusable data type definitions for API specifications
Simplifying content negotiation in resource-based APIs
Generating multiple output formats (JSON, XML, YAML) from a single source
Validating data structures in API Blueprint projects

Not Ideal For

Projects requiring full JSON Schema validation with advanced keywords like uniqueItems or exclusiveMinimum
Teams working primarily with binary data or custom serialization formats not covered by basic types
Environments where direct YAML/JSON editing is preferred and a Markdown abstraction adds unnecessary overhead

Pros & Cons

Pros

Human-Readable Syntax

Uses familiar Markdown lists and headers to define data structures, making them easy to write and discuss in plain text, as shown in examples like the simple 'Product' object.

Multi-Format Generation

Can output JSON, JSON Schema, XML, or YAML from a single MSON description, facilitating markup-agnostic resource descriptions and content negotiation.

Reusable Type Definitions

Supports named types, references, and mixins for DRY data modeling, demonstrated in the 'Address' and 'User' examples with the 'Include' keyword.

Validation Integration

Enables validation of HTTP payloads through derived JSON Schema, making it a natural fit for API Blueprint projects and API documentation.

Cons

Limited JSON Schema Coverage

The README explicitly states it does not support all JSON Schema keywords, such as uniqueItems or exclusiveMinimum, restricting its use for complex validation scenarios.

Syntax Complexity for Edge Cases

Advanced features like multi-line descriptions require careful use of keywords like 'Properties' to avoid parsing conflicts, which can be error-prone and less intuitive.

Ecosystem Niche

Developed primarily for API Blueprint by Apiary, which may result in limited tooling and community support outside of API documentation contexts.

MSON

What is MSON?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?

MSON

What is MSON?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?