Google YouTube Data

YouTube

Operated by Sourcelane✓ verified

Converts lists of YouTube search queries into structured video metadata using the official YouTube Data API v3. For each (query, video) pair it returns one row containing title, channel attribution, publish date, description, best-available thumbnail URL, view/like/comment statistics parsed as integers, duration provided both as raw ISO 8601 and as seconds, and the canonical video URL. Supports sorting by relevance, date, rating, view count, or title, optional publish-date filtering, and emits a single error row if an individual query fails so the run continues. Outputs are current live API results and are formatted for keyword-level pivoting, trend analysis, and channel-level comparisons.

Verified Sep 28, 3:55 AM

$0.01

per search query

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

What people use it for

Channel competitive analysis: pull top-ranking videos for keyword sets to compare channel performance and dominance
Content discovery: surface newest, high-engagement videos in a niche for content ideation
Trend tracking: build time-series results of view-count growth across topics
Influencer research: identify creators ranking for target keywords and rank by subscribers/engagement metrics
Video SEO results: assemble training data of titles, descriptions, durations, and view/count metrics for ranking models
Ad targeting: compile lists of high-traffic videos by topic for placement campaigns

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://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"google-youtube-data","params":{"maxResultsPerQuery":5},"maxResults":10}'

Request params

Field	Type	Required	Description
`maxResultsPerQuery`	integer	optional	Number of videos to return per query (1-50). Capped at 100 per call.
`order`	string	optional	Sort order applied to YouTube search results.
`publishedAfter`	string	optional	Optional ISO 8601 datetime - only return videos published after this moment.

Each result contains

Field	Type	Description
`query`	string	Query
`videoId`	string	Video Id
`status`	string	Status
`title`	string	Title
`channelId`	string	Channel Id
`channelTitle`	string	Channel Title
`publishedAt`	string	Published At
`description`	string	Description
`thumbnailUrl`	string	Thumbnail Url
`viewCount`	integer	View Count
`likeCount`	integer	Like Count
`commentCount`	integer	Comment Count
`durationIso`	string	—
`durationSeconds`	integer	—
`url`	string	—
`error`	null	—

Use Google YouTube Data 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://api.usesourcelane.com/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://api.usesourcelane.com/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://api.usesourcelane.com/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://api.usesourcelane.com/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://usesourcelane.com/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"google-youtube-data","params":{"maxResultsPerQuery":5},"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://api.usesourcelane.com/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "google-youtube-data",
        "params": {"maxResultsPerQuery":5},
        "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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