Give it a page URL and it writes the schema.org block for that page, then runs a validator over its own output before you see it.
Free, no login, no email. Nothing stored beyond a 24 hour cache. Markdown copy · API and MCP
Paste the page you want marked up
The generator reads that page and nothing else. A page with real content on it produces a much better block than a thin landing page.
It picks a type and writes the block
A model chooses the schema.org type that fits the page, then fills it in using only what the page states. Anything it cannot find on the page is left out.
Read the checks, then copy
The same validator that powers our JSON-LD Validator runs over the generated block. Read what it says, then copy the script tag into your page.
It is that it is confident. A language model asked to describe a product page will produce something that reads like a complete, professional block. The dangerous part is the property it had no way to know. If your page never states a rating, a model that fills in aggregateRating anyway has not made a small mistake. It has written a claim about your business that your own page contradicts.
Search engines treat that as a specific category of problem. Structured data that does not match visible page content is a spam signal, and the manual action that follows applies to the site, not to the one page that carried the bad block. Sites have lost every rich result they had over an invented review count somebody pasted in from a generator without reading it. The cost of the mistake is wildly out of proportion to how easy it is to make.
The model behind this tool is instructed to describe only what the page actually says, and to omit any property it cannot support from the text in front of it. A sparser block that is true is worth more than a full one that is not. If you generate markup here and a property you expected is missing, that is usually the tool telling you something useful: the page does not state it anywhere a reader could see it either.
Then the same checks that power our JSON-LD Validator run over the generated block before you ever see it. Generation and correctness are different problems, and a model can write something fluent that still misses a property Google requires or uses a date format that gets discarded on read. Running the validator afterwards moves that discovery from months later to before you paste.
This is the part no tool can do for you. Structured data is a claim you are making to search engines and answer engines about your own site, in a format your visitors never see. Nobody else is going to notice if it is subtly wrong. Read the block, check that the type is the one you meant, and check that the description says what you would say. It takes a minute, and it is the difference between markup you have published and markup you have merely pasted.
Read it before you ship it. That is not a disclaimer, it is the workflow. The block is grounded in the text of your page, so most of it will be right, but you are the only one who can confirm that a description matches your intent or that a type is the one you meant. Structured data is a claim you are making to search engines about your own site, and it should be a claim you have read.
The same run this page does, as an HTTP endpoint and as the MCP tool generate_json_ld. No account, no API key. Full reference.
curl -sS https://usesuperflow.ai/api/tools/json-ld-generator \
-H 'Content-Type: application/json' \
-d '{"url":"example.com"}'Returns { ok, report: { detectedType, jsonLd, jsonLdString, validation: { findings[], passed }, model } }. 10 runs per hour per IP. Allow up to 75 seconds.
claude mcp add --transport http superflow https://usesuperflow.ai/api/mcpThen ask your agent for generate_json_ld. Setup for Claude Desktop, Cursor and VS Code is on the reference page.
No login, no email, no ads. Same as this one.
Superflow agents check the structured data on every page you ship, on every change, and tell you when a block breaks, contradicts the page, or quietly disappears.