YouTube Transcript Scraper

YouTube

Operated by Sourcelane✓ verified

A tool for extracting full plain-text transcripts and timestamped caption segments from YouTube videos, returning structured transcript text plus segment-level timing (milliseconds), language metadata (language codes, and whether captions are human-written or auto-generated), and a list of all available caption tracks per video. Outputs are suitable for search, summarization, LLM input, building chapter markers, and export to common structured formats.

Verified Sep 28, 12:11 AM

$0.0001

per transcript

Up to 100 per call. Only pay for results returned; failed calls are refunded.

What people use it for

Content repurposing: turn long videos into blog posts, newsletters, or social threads with timestamped quotes
SEO research: analyze competitor video scripts and topics for keyword and topic gaps
Accessibility: generate searchable text archives of training videos, lectures, and webinars
Language learning: pull dual-language transcripts for the same video to build study material
Podcast and interview notes: feed transcripts into summarizers to produce show notes and chapter markers

Trust & reliability

7d uptime trend

Window	Uptime	Success rate	p50	p95
24h	—	—	—	—
7d	—	—	—	—
30d	—	—	—	—

Calling contract

Call it through Sourcelane's gateway or MCP server. We run the connector, apply your agent's spend guardrails, and bill only the results returned.

Call it via Sourcelane

curl -X POST https://cool-puffin-608.convex.site/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"youtube-transcript-scraper","params":{"videoUrls":["https://www.youtube.com/watch?v=jNQXAC9IVRw"]},"maxResults":10}'

Request params

Field	Type	Required	Description
`videoUrls`	array	required	One or more YouTube video URLs (youtube.com/watch?v=..., youtu.be/..., or youtube.com/shorts/...). Up to 10 per run.
`languages`	array	optional	BCP-47 language codes in preference order, e.g. en, es, fr. The first language with available captions for a video will be used for the transcript and segments fields.
`preferManualCaptions`	boolean	optional	When both manual and auto-generated captions exist for a language, use the human-written ones. Turn off to always pick whichever is available.

Each result contains

Field	Type	Description
`inputUrl`	string	Input Url
`videoId`	string	Video Id
`title`	string	Title
`durationSeconds`	integer	Duration Seconds
`uploader`	string	Uploader
`language`	string	Language
`isAutoGenerated`	boolean	Is Auto Generated
`transcript`	string	Transcript
`segments`	array	—
`availableLanguages`	array	Available Languages
`proxyUsed`	string	Proxy Used
`status`	string	Status
`error`	null	—

Use YouTube Transcript Scraper from Claude, ChatGPT or Cursor

Pick your tool and connect in under a minute. Then just ask — for example: “Get the transcript of this video and turn it into a blog outline: <url>”

Connect Claude

Web, desktop and mobile. Paste one URL.

1Copy your personal connector URL
2In Claude open Settings → Connectors → Add custom connector
3Paste the URL and click Add — done

Manual setup (config files, REST, Python) +

Claude Code

Adds the Sourcelane MCP server with your key as a header.

terminal

claude mcp add --transport http sourcelane https://cool-puffin-608.convex.site/mcp \
  --header "Authorization: Bearer sl_live_your_agent_key"

Claude Desktop (config file)

Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.

claude_desktop_config.json

{
  "mcpServers": {
    "sourcelane": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://cool-puffin-608.convex.site/mcp",
        "--header",
        "Authorization:${AUTH_HEADER}"
      ],
      "env": {
        "AUTH_HEADER": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

Cursor & Windsurf

Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).

mcp.json

{
  "mcpServers": {
    "sourcelane": {
      "url": "https://cool-puffin-608.convex.site/mcp",
      "headers": {
        "Authorization": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

VS Code

Save as .vscode/mcp.json. VS Code prompts for your key once.

.vscode/mcp.json

{
  "servers": {
    "sourcelane": {
      "type": "http",
      "url": "https://cool-puffin-608.convex.site/mcp",
      "headers": {
        "Authorization": "Bearer ${input:sourcelane-key}"
      }
    }
  },
  "inputs": [
    {
      "type": "promptString",
      "id": "sourcelane-key",
      "description": "Sourcelane agent key",
      "password": true
    }
  ]
}

ChatGPT Custom GPT (Actions)

Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.

OpenAPI schema URL

https://sourcelane-amber.vercel.app/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://cool-puffin-608.convex.site/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"youtube-transcript-scraper","params":{"videoUrls":["https://www.youtube.com/watch?v=jNQXAC9IVRw"]},"maxResults":10}'

Python, LangChain, CrewAI, OpenAI Agents SDK…

Wrap the REST call as a tool, or point an MCP client at the endpoint.

python

import requests

res = requests.post(
    "https://cool-puffin-608.convex.site/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "youtube-transcript-scraper",
        "params": {"videoUrls":["https://www.youtube.com/watch?v=jNQXAC9IVRw"]},
        "maxResults": 10,
    },
    timeout=300,
)
body = res.json()
print(body["receipt"]["chargedMicros"], "micro-USD for", body["receipt"]["results"], "results")
print(body["data"])

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