Markdown to Structured Data Article Converter
Turn Markdown articles into clean Schema.org JSON-LD for articles, blog posts, and technical documentation.
Converter
Results
Extracted metadata
Introduction
Structured data helps search systems understand article content. However, writing JSON-LD manually can be repetitive, especially for articles with authors, dates, images, and descriptions.
This converter extracts common fields from Markdown and generates clean Schema.org markup locally.
How it works
The tool parses simple front matter and Markdown body content. It extracts the title, description, author, dates, tags, and image where possible, then builds a JSON-LD object.
- Front matter fields such as
title,description, anddateare supported. - The first H1 is used if no front matter title exists.
- The first paragraph is used for description if no description exists.
- The first Markdown image is used if no image override is provided.
How to use
- Paste your Markdown article.
- Choose the article type.
- Optionally add canonical, author, publisher, and image overrides.
- Generate the JSON-LD.
- Copy the JSON-LD or HTML script snippet.
Practical example
Front matter example:
---
title: Understanding Service Worker Caching
description: Learn how service worker cache strategies affect offline support.
author: Nasimul Haq
date: 2026-08-01
tags: service worker, caching, pwa
---Use cases
- Preparing blog post structured data.
- Converting technical articles into Schema.org markup.
- Generating JSON-LD for static site templates.
- Reviewing article metadata before publishing.
- Creating documentation examples for SEO teams.
Best practices
- Keep headlines concise.
- Write accurate descriptions.
- Use absolute image and canonical URLs.
- Match structured data to visible page content.
- Test output with structured data validation tools.
Common mistakes
- Adding structured data that does not match the article.
- Using relative image URLs.
- Missing date fields.
- Overusing keywords in structured data.
- Assuming structured data guarantees rich results.
Limitations
- The front matter parser supports simple key-value fields.
- Complex YAML structures are not fully parsed.
- The tool does not validate against every Schema.org constraint.
- Search engines may apply additional eligibility rules.
Browser compatibility
The tool works in current versions of major browsers using standard JavaScript string processing.
FAQ
Is my Markdown uploaded?
No. Conversion happens locally in your browser.
Does it support front matter?
Yes, simple front matter fields such as title, description, author, date, updated, tags, image, canonical, and publisher are supported.
Will this guarantee rich results?
No. Structured data eligibility depends on search engine systems and content quality.
Can I use it for static site generators?
Yes. The generated JSON-LD can be used as a reference or embedded directly in templates.