Tabstack
Mozilla · Coding
Tabstack is a managed web execution API built by Mozilla that handles data extraction and browser automation in a single call. You send it a URL, a schema, a question, or a plain-language task, and it returns structured data, cited answers, or a completed browser flow. Think of it as a web scraping API that also knows how to click and type. It's aimed at developers and AI agent builders who need live web access without running their own scraping stack, browser fleet, or LLM pipeline.
About Tabstack
What Is Tabstack
Tabstack is a web data and browser automation API for AI agent builders. The core promise is simple: instead of wiring up a scraper, a headless browser, and a language model yourself, you call one endpoint and let Tabstack run the whole thing. Mozilla backs the project, and the browser engine under the hood, Pilo, is open source.
The main problem it solves is the glue work behind agentic browsing. Anyone who's built a scraping pipeline knows the drill: pages change their markup, JavaScript blocks your fetch, and the maintenance never ends. Tabstack runs rendering, reasoning, and schema enforcement server-side, so your app just gets clean output back.
Among AI agent tools, that's the differentiator. Most of them still expect you to supply the browser.
There's a real limit worth knowing. Tabstack is a developer tool. If you don't write code at all, this isn't a drag-and-drop app. Everything runs through REST endpoints, and you'll want at least basic familiarity with APIs to get value from it.
Getting Started
- Visit the Tabstack Console and sign in, or create an account. Google sign-in works, and no credit card is needed to start.
- Open the API Keys section, click Manage API Keys, then Create New API Key. Give it a name like "Development" and copy the value somewhere secure.
- Store the key as an environment variable (
TABSTACK_API_KEY) so you aren't hardcoding secrets into scripts you'll share later. - Send your first request to the markdown extraction endpoint with a test URL, and confirm the response comes back with clean content.
- Install the TypeScript or Python SDK once the raw calls work, then move on to schema-based extraction or automation tasks.
Product Information
A quick look at Tabstack's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- AI agent developers
- Backend and full-stack engineers
- Data teams building dashboards
Tasks
- Structured data extraction
- Web research with citations
- Browser automation
- Markdown conversion for RAG
Scenarios
- Running a price monitor on a fixed schedule
- Enriching inbound leads
- Completing booking or checkout flows
Key features
One-Call Extraction and Automation
Tabstack bundles rendering, reasoning, and schema enforcement into single endpoints. You pass a URL and a schema to /extract/json and get structured output back, or pass a task to /automate and get a completed browser flow. The value is what you don't build. No browser provisioning, no pipeline to babysit.
Research Agent With Inline Citations
The /research endpoint answers a question from the live web and cites every claim to its source. Source selection, reading, synthesis, and citation all happen inside the call, so you can ship a research feature without building the retrieval backend behind it. Results stream over SSE. That helps with longer answers.
Structured JSON From Any Page
Define the output shape your stack needs and Tabstack enforces it before the response returns. You can ask for nested fields, like product sizes with an in-stock flag for each one, rather than settling for a flat dump of page text. Clean data in, clean data out.
Browser Automation Without Infrastructure
The /automate endpoint carries out plain-language tasks on live pages: navigating, clicking, filling forms, and finishing multi-step flows on sites you don't control. Interactive mode pauses for human input when a step needs a judgment call, which keeps risky actions under oversight.
Pilo Browser Engine
Tabstack runs on Pilo, Mozilla's open-source browser engine. According to Mozilla, Pilo uses 60 to 80 percent fewer tokens than screenshot-based browsing. Does that matter? If you're paying per token on a model behind your agent, yes, a lot. Fewer tokens also means faster loops.
Markdown Conversion for Pipelines
/extract/markdown turns any page into clean Markdown your models can read directly. It's the pragmatic option for feeding documentation, articles, or product pages into a RAG pipeline without maintaining a custom scraper.
SDKs, MCP, and CLI Support
Beyond plain REST calls, Tabstack ships a TypeScript SDK and a Python SDK, plus MCP and CLI integrations. If your agent stack already speaks MCP, adding web access takes a configuration line rather than a new service.
Pros and cons
Pros
- Runs the browser, model, and orchestration on its side, so you don't provision any of it.
- Free tier gives 10,000 credits with no credit card required to start.
- Every extraction result can be shaped to your own schema, which cuts post-processing.
- Mozilla-backed with an open-source browser engine you can inspect.
- Data policy states your content is never sold and never trained on.
Cons
- It's a developer API only, so non-coders can't use it directly.
- Published pricing above the free credits isn't clear from the site, so budget planning needs a sales conversation.
- Automation on third-party sites can still break when a page changes, which means ongoing testing on your side.
Frequently asked questions
Tabstack lets apps and AI agents read and act on live websites through one API. Common uses include structured data extraction, web research with citations, and browser automation like filling forms or finishing checkout flows.
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