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Documentation Index

Fetch the complete documentation index at: https://docs.veedcrawl.com/llms.txt

Use this file to discover all available pages before exploring further.

/v1/extract is an async AI operation that watches the whole video and returns a structured answer to your prompt. POST to enqueue the job, then poll until the result is ready. If you’re using the MCP server, polling is handled automatically and your agent receives the finished result directly. Credits: 10 credits per extraction.

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Step 1 — Enqueue the job

POST https://api.veedcrawl.com/v1/extract
This endpoint requires an x-api-key header and Content-Type: application/json.

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Body parameters

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url
string
required
The full public video URL, or a direct media file URL.
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prompt
string
required
What to extract or analyze — for example: "List all product names", "Summarize in 3 sentences", or "What is the hook?".
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lang
string
Optional language hint for transcription — e.g. "en", "es", "ur".
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schema
object
Optional JSON Schema object that constrains the shape of resultJson. Use this to get typed, predictable output that slots directly into your application.

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Example

curl -X POST "https://api.veedcrawl.com/v1/extract" \
  -H "x-api-key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://www.youtube.com/watch?v=...", "prompt": "Extract all product names shown"}'

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Response

{
  "jobId": "job_xyz456",
  "status": "queued"
}

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Step 2 — Poll for the result

GET https://api.veedcrawl.com/v1/extract/{jobId}

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Example

curl "https://api.veedcrawl.com/v1/extract/job_xyz456" \
  -H "x-api-key: YOUR_KEY"

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Response when complete

{
  "jobId": "job_xyz456",
  "status": "completed",
  "resultJson": {
    "products": ["iPhone 16 Pro", "AirPods Pro 2"]
  }
}
Poll until status is "completed" or "failed".

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Example prompts

The prompt field is free-form. Here are prompts that work well:
  • "Extract the hook, main argument, and call to action"
  • "List every product mentioned with the timestamp it appears"
  • "What claims does the speaker make? Rate each one as factual, opinion, or unverified"
  • "Rewrite this as a Twitter thread"

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Using JSON Schema for typed output

Pass a schema field to constrain the structure of resultJson. This is useful when you need the result to conform to a specific interface in your application. 
curl -X POST "https://api.veedcrawl.com/v1/extract" \
  -H "x-api-key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://www.youtube.com/watch?v=...",
    "prompt": "List every product mentioned in the video",
    "schema": {
      "type": "object",
      "properties": {
        "products": {
          "type": "array",
          "items": { "type": "string" }
        }
      },
      "required": ["products"]
    }
  }'
If you’re using the Veedcrawl MCP server, polling is handled automatically. Your agent receives the completed extraction result without any extra logic.