Sourcelane

YouTube Chapters & Timestamps Generator

YouTube

Operated by Sourcelane✓ verified

Generates paste-ready YouTube chapter timestamp blocks, structured chapter metadata, SEO-friendly video descriptions and optimized tag lists by analyzing a video's transcript. The connector detects topic-change points in transcripts to produce chapter start times and concise titles, builds a formatted timestamp block for descriptions, produces a 120–250 word SEO-focused description with the main keyword up front, appends chapters to the description, and generates a trimmed set of search tags that fit YouTube tag-length limits. It enforces YouTube chapter rules (starts at 0:00, minimum number of chapters, minimum chapter duration, chronological order, and proper m:ss or h:mm:ss formatting), preserves existing chapter data for comparison, supports transcript languages and optional translation of chapter titles, descriptions and tags, processes long-form transcripts in one pass for extended content, and returns video metadata plus per-item processing status and error information.

Verified Sep 28, 12:10 AM

$0.05

per video

Up to 20 per call. Only pay for results returned; failed calls are refunded.

What people use it for

Trust & reliability

7d uptime trend
WindowUptimeSuccess ratep50p95Calls
24h————0
7d————0
30d————0

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-chapters-generator","params":{"videoUrls":["https://www.youtube.com/watch?v=8jPQjjsBbIc"]},"maxResults":10}'

Request params

FieldTypeRequiredDescription
videoUrlsarrayrequiredYouTube video URLs or 11-character video IDs, one per line. Up to 50 per run. The video needs captions (manual or auto-generated).
chapterStylestringoptionalHow chapter titles are written. Keyword-rich leads each title with the phrases viewers search for, which helps chapters appear as key moments in Google and YouTube search.
minChapterSecondsintegeroptionalShortest allowed chapter. YouTube requires at least 10 seconds per chapter; 30-60 seconds reads better for most videos.
maxChaptersintegeroptionalUpper limit on chapters per video. YouTube requires at least 3. The count scales with video length up to this limit.
outputLanguagestringoptionalLanguage for chapter titles, description and tags, e.g. English, Spanish, German. Leave empty to match the video's language.
generateDescriptionbooleanoptionalAlso write a 120-250 word YouTube description with the main keyword in the first line, plus a paste-ready version with the chapters appended.
generateTagsbooleanoptionalAlso suggest 12-20 YouTube tags, trimmed to fit YouTube's 500-character tag limit.
transcriptLanguagesarrayoptionalOptional caption language codes to use, in order of preference (e.g. en, es). Leave empty to use the video's own spoken language automatically.
modelstringoptionalLanguage model that reads the transcript and writes the chapters. The default handles very long videos in one pass.

Each result contains

FieldTypeDescription
inputUrlstringInput URL
videoIdstring—
urlstringURL
titlestringTitle
channelNamestringChannel
durationSecondsintegerDuration (s)
hasExistingChaptersbooleanHad chapters
existingChaptersarray—
chaptersarray—
chaptersTextstringChapters (paste-ready)
seoDescriptionstringSEO description
descriptionWithChaptersstring—
tagsarrayTags
chapterStylestring—
transcriptLanguagestringTranscript language
transcriptIsAutoGeneratedboolean—
transcriptTruncatedboolean—
modelstring—
statusstringStatus
errornullError

Use YouTube Chapters & Timestamps Generator 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.

  1. 1Copy your personal connector URL
  2. 2In Claude open Settings → Connectors → Add custom connector
  3. 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-chapters-generator","params":{"videoUrls":["https://www.youtube.com/watch?v=8jPQjjsBbIc"]},"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-chapters-generator",
        "params": {"videoUrls":["https://www.youtube.com/watch?v=8jPQjjsBbIc"]},
        "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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