Schema-driven extraction
Define the JSON shape you need and send a URL. Tabstack enforces the schema on the server side and returns output that matches it, even when the source page changes.
Tabstack
Tabstack’s Structured Data Extraction API turns a URL into schema-matched JSON, with a related instruction-based generation flow for outputs that require reasoning. It is aimed at teams that need structured web data without maintaining parsing, browser, or LLM orchestration layers.
Structured Data Extraction API
Tabstack’s Structured Data Extraction API turns a URL into JSON that matches a schema you define. The product is built for teams that need consistent structured output from web pages without maintaining their own parsing logic, browser pipeline, or downstream LLM orchestration.
The pages on the site show two closely related workflows: `/extract/json` for direct schema-matched extraction, and `/generate/json` for cases where instructions and reasoning are needed on top of the page content. The same platform also exposes Markdown output, research with citations, and browser automation, but this page is focused on the structured extraction use case.
Features
Multiple structured output modes
Use `/extract/json` for fixed-shape data, `/extract/markdown` for page text, and `/generate/json` when you want instructions layered on top of the source page.
Works across dynamic pages
The site says extraction works on server-rendered, client-rendered, and JavaScript-heavy pages, so the workflow is not limited to static HTML.
Reasoned structured answers
`/generate/json` adds instructions to the URL-based workflow, making it useful when the task requires interpretation rather than a direct field pull.
Request-level control
Control freshness and retrieval behavior with `nocache`, `effort`, and `geo_target`, including fresh fetches and country-specific views.
Developer access options
A TypeScript SDK is shown in the product examples, and the pricing page also lists Python SDK, MCP, and CLI as access options for the broader platform.
Use Cases
Competitive pricing and catalog monitoring
Pull pricing tables, product specs, inventory states, or other page data into a fixed JSON shape for dashboards and downstream systems.
Lead and account enrichment
Turn a domain or product page into normalized company, product, or contact data for enrichment pipelines.
Knowledge base ingestion
Feed product pages, docs, and articles into retrieval or indexing pipelines using structured JSON or Markdown instead of custom scraping code.
Structured analysis from web pages
Use `/generate/json` when the page alone is not enough and the result needs a structured interpretation, such as explaining what a pricing page implies about segmentation.
Research and browser workflows
For teams that need adjacent workflows, the same platform also supports cited web research and browser automation on live pages.
Pros and Cons
Pros
- Returns schema-matched JSON from a URL-based call, which reduces the need for custom parsing code.
- Supports both direct extraction and instruction-based generation for tasks that need light reasoning.
- Documents behavior on dynamic and JavaScript-heavy pages, not just static HTML.
- Provides request controls such as freshness and geographic targeting.
- Backed by public pricing options, including a free trial and paid plans.
Cons
- The source pages do not publish a complete integration matrix, so SDK and auth details are only partially documented in the collected evidence.
- Pricing is public, but exact usage costs depend on credits and plan selection rather than a single fixed per-request price.
FAQ
How do you use Tabstack in an app?
Yes. The source pages show a TypeScript SDK and example calls for the extraction and research endpoints, along with API endpoints documented for `/extract/json`, `/extract/markdown`, `/generate/json`, `/research`, and `/automate`.
What does the structured extraction API return?
The structured extraction workflow is designed for a URL plus a JSON schema. Tabstack returns JSON that matches the schema, and the site also shows a related `/generate/json` flow for instructions-based structured output.
What kinds of pages can it handle?
The home page shows extraction working on server-rendered, client-rendered, and JavaScript-heavy pages. It also mentions clean Markdown output when needed.
Is there a free tier or paid plan?
Pricing is shown publicly on the site: there is a free trial with 10,000 credits, an Individual plan, Team and Pro plans with included credits, and an Enterprise plan with custom pricing.
What integrations and output formats are documented?
The source materials do not describe a published list of SDKs, authentication methods, or output formats beyond the examples shown on the pages. The clearest documented outputs are schema-matched JSON, clean Markdown, cited research answers, and completed browser tasks.
Quick Facts
- Category
- Developer Tool
- Product type
- Structured data extraction API
- Core workflow
- Define a schema, pass a URL, get matching JSON back
- Related outputs
- JSON, Markdown, cited research answers, browser tasks
- Platform
- Web API with TypeScript examples
- Pricing
- Free trial and paid plans listed publicly
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