More API

Extract

Return structured JSON from a known page. In CRW, extraction is a scrape mode: use formats: ["json"] and provide a schema that describes the fields you want back.

Best for: schema-first output
Route: /v1/scrape
Start with: a tiny schema
View Scrape Try in Playground
Try it in the Playground
Verify the page before you verify the schema
A reliable extraction flow is simple: confirm the page scrapes cleanly, then add the smallest possible schema, then expand only if the page really contains the extra fields you want.
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Extracting structured data with CRW

/v1/scrape

POST /v1/scrape

Authentication:

  • Hosted: send Authorization: Bearer YOUR_API_KEY
  • Self-hosted: only required when auth.api_keys is configured

Installation

Extraction uses the same HTTP route as scrape, so you can use the same client code and only change the payload.

Basic usage

Start with this request:

{
  "url": "https://example.com/product/123",
  "formats": ["json"],
  "jsonSchema": {
    "type": "object",
    "properties": {
      "title": { "type": "string" },
      "price": { "type": "string" },
      "availability": { "type": "string" }
    },
    "required": ["title"]
  }
}

:::tabs ::tab{title="Python"}

import requests

resp = requests.post(
    "https://fastcrw.com/api/v1/scrape",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
        "url": "https://example.com/product/123",
        "formats": ["json"],
        "jsonSchema": {
            "type": "object",
            "properties": {
                "title": {"type": "string"},
                "price": {"type": "string"},
                "availability": {"type": "string"},
            },
            "required": ["title"],
        },
    },
)

print(resp.json()["data"]["json"])

::tab{title="Node.js"}

const resp = await fetch("https://fastcrw.com/api/v1/scrape", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    url: "https://example.com/product/123",
    formats: ["json"],
    jsonSchema: {
      type: "object",
      properties: {
        title: { type: "string" },
        price: { type: "string" },
        availability: { type: "string" }
      },
      required: ["title"]
    }
  })
});

const body = await resp.json();
console.log(body.data.json);

::tab{title="cURL"}

curl -X POST https://fastcrw.com/api/v1/scrape \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url":"https://example.com/product/123",
    "formats":["json"],
    "jsonSchema":{
      "type":"object",
      "properties":{
        "title":{"type":"string"},
        "price":{"type":"string"},
        "availability":{"type":"string"}
      },
      "required":["title"]
    }
  }'

:::

Response

{
  "success": true,
  "data": {
    "json": {
      "title": "Widget",
      "price": "$19.99",
      "availability": "In stock"
    },
    "metadata": {
      "sourceURL": "https://example.com/product/123",
      "statusCode": 200,
      "elapsedMs": 846
    }
  }
}

Parameters

Field Type Default Description
url string required Target page URL
formats string[] required Use ["json"] for the canonical extraction path
jsonSchema object required JSON schema describing the fields you want back
extract object -- Firecrawl-compatible wrapper; extract.schema is accepted
llmApiKey string -- Per-request BYOK credential
llmProvider string server default anthropic or openai
llmModel string server default Extraction model override
onlyMainContent boolean true Keep extraction focused on the main content block
cssSelector string -- Narrow the page before extraction
xpath string -- Narrow the page before extraction

:::note Firecrawl-compatible aliases formats: ["extract"] and formats: ["llm-extract"] are accepted, but ["json"] is the canonical CRW shape. :::

:::warning On self-hosted deployments, JSON extraction requires either [extraction.llm] in config.toml or a per-request llmApiKey. Without one of those, CRW returns an extraction error instead of guessed output. :::

Schema design

The easiest extraction schema is a small one:

  • ask for the fields you actually need,
  • keep field types simple on the first pass,
  • avoid optional fields until the required ones are stable.

Large schemas are harder to debug because you cannot tell whether the issue is the page, the schema, or both.

Extraction quality

Use this workflow:

  1. scrape the page as markdown,
  2. verify the target content is present,
  3. add a minimal schema,
  4. expand the schema only after the first JSON result looks right.

If the underlying page scrape is weak, the JSON extraction will also be weak.

BYOK and provider control

Use llmApiKey, llmProvider, and llmModel only when you need per-request control. For most users, server defaults are the right starting point once [extraction.llm] is configured.

Common production patterns

  • Validate the target with markdown first, then add extraction.
  • Keep the schema as small as possible on the first pass.
  • Narrow the page with cssSelector only when the default extraction is too noisy.
  • Use BYOK only when you need per-request provider separation.

Common mistakes

  • Sending formats: ["json"] without a schema
  • Designing a schema that assumes more structure than the page really contains
  • Debugging extraction before confirming the underlying scrape succeeded
  • Treating extraction as a separate route instead of a scrape mode

When to use something else

  • Use Scrape when prose or markdown is enough
  • Use Map when you need discovery before extraction
  • Use Crawl when you need schema-based extraction across many pages