---
title: Looking for a Firecrawl Alternative? | Tabstack
description: Tabstack is a structured output API for AI agents. If you need schema-enforced JSON extraction, AI transformation, or autonomous research instead of site-wide crawling, here is how it compares.
---

Firecrawl is good at what it does: crawling entire sites and producing markdown. But developers running into its limits usually hit the same two walls:

1. **No AI transformation step.** Firecrawl extracts content and crawls sites. There’s no equivalent to Tabstack’s `/generate/json`: fetch a URL, apply custom AI instructions, and return structured output in one call. If categorization, scoring, or transformation is part of the extraction job, that’s a separate LLM call you write yourself.
2. **No multi-source cited research.** Firecrawl’s `/agent` does autonomous web discovery — you describe what you want, it finds and extracts it. That’s different from Tabstack’s `/research`: a question in, multi-source synthesis out, with citations. Firecrawl doesn’t have that.

Tabstack is a direct alternative for the extraction and research use cases. Here’s what you need to know.

---

## Schema-driven extraction, included

Tabstack’s `/extract/json` is schema-driven: you define the shape of the data you want, pass a URL, get back exactly that structure. No separate subscription. No natural language prompt to tune.

```
import Tabstack, { APIError } from '@tabstack/sdk'


const client = new Tabstack({ apiKey: process.env.TABSTACK_API_KEY })


const result = await client.extract.json({
  url: 'https://example.com/pricing',
  json_schema: {
    type: 'object',
    properties: {
      plans: {
        type: 'array',
        items: {
          type: 'object',
          properties: {
            name: { type: 'string', description: 'Plan name' },
            price: { type: 'number', description: 'Monthly price in USD' },
            features: {
              type: 'array',
              items: { type: 'string' },
              description: 'Included features'
            }
          }
        }
      }
    }
  }
})


console.log(result.plans)
```

The schema is the spec. The API delivers it.

---

## Autonomous cited research - not available in Firecrawl

Tabstack’s `/research` endpoint takes a question, autonomously searches the web, reads and synthesizes multiple sources, and returns a cited answer. One API call.

```
const stream = await client.agent.research({
  query: 'What are the current pricing models for cloud browser automation APIs?',
  mode: 'fast'
})


for await (const event of stream) {
  if (event.event === 'complete') {
    console.log(event.data.report)
    const cited = event.data.metadata.citedPages ?? []
    console.log(`Cited ${cited.length} sources:`)
    for (const page of cited) {
      console.log(`- ${page.title ?? '(untitled)'}: ${page.url}`)
    }
  }
  if (event.event === 'error') {
    throw new Error(event.data.error.message)
  }
}
```

No orchestration code. No source selection. No citation pipeline to build. Firecrawl’s `/agent` handles autonomous web discovery and extraction, but it’s scoped to extraction, not multi-source research with citation synthesis across arbitrary sources in a single call.

---

## AI transformation - also included

Tabstack’s `/generate/json` fetches a URL, applies your AI instructions, and returns structured output in one call. Categorize, summarize, score, rewrite. No separate LLM step.

```
try {
  const result = await client.generate.json({
    url: 'https://competitor.com/blog',
    instructions: 'For each article, identify the target audience and assign a relevance score 1-10 for a developer focused on AI agents.',
    json_schema: {
      type: 'object',
      properties: {
        articles: {
          type: 'array',
          items: {
            type: 'object',
            properties: {
              title: { type: 'string' },
              target_audience: { type: 'string' },
              relevance_score: { type: 'number', description: '1-10 score for AI agent developers' }
            }
          }
        }
      }
    }
  })
  console.log(result.articles)
} catch (err) {
  if (err instanceof APIError) {
    console.error(`API error ${err.status}: ${err.message}`)
    throw err
  }
  throw err
}
```

---

## What Firecrawl still does better

Being direct: if site-wide crawling is the primary use case, Firecrawl is the stronger choice. Tabstack is a per-URL API, with no recursive link following, no sitemap traversal, no 10,000-page site ingestion in one call.

If your job is bulk content ingestion into a vector store, Firecrawl’s `/crawl` is built for that. Tabstack is not.

If your job is extracting structured data from specific pages, transforming content with AI, or running autonomous research, Tabstack is the cleaner path.

---

## Pricing comparison

|                       | Tabstack                       | Firecrawl                                                                                   |
| --------------------- | ------------------------------ | ------------------------------------------------------------------------------------------- |
| Structured extraction | Included, schema-first         | Available via `/scrape` (schema-driven, single pages) or `/agent` for autonomous multi-page |
| AI transformation     | Included (`/generate/json`)    | Not available - requires a separate LLM call                                                |
| Autonomous research   | Included (`/research`)         | Partial - `/agent` for autonomous extraction; no citation synthesis                         |
| Markdown extraction   | Included (`/extract/markdown`) | Core product                                                                                |
| Site-wide crawling    | Not available                  | Core product                                                                                |

---

## SDK coverage

Tabstack has official SDKs for TypeScript and Python. Installation:

Terminal window

```
npm install @tabstack/sdk     # TypeScript
pip install tabstack           # Python
```

---

## Get started

API key at [console.tabstack.ai](https://console.tabstack.ai). First structured extraction in under 5 minutes.

[Full documentation](https://docs.tabstack.ai)