TikTok Search Scraper

TikTok

Operated by Sourcelane✓ verified

A keyword-driven TikTok search scraper that performs user-like keyword queries and extracts ranked, structured video-level data from TikTok search results. The connector returns one record per video in TikTok's search order and captures search ranking context together with video metadata (identifiers, direct URLs, text descriptions, hashtags, duration, cover image, post date, region), engagement metrics (plays/views, likes, comments, shares, saves/collections, downloads/reposts), author metadata (handle, display name, verification status, follower counts, biography), and music metadata (track identifiers, title, artist). Results reflect live TikTok search at the time of the run and are optimized for keyword analysis and competitive monitoring.

Verified Sep 28, 12:10 AM

$0.002

per result

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

What people use it for

Trend research — identify which videos currently rank for specific keywords
Influencer discovery — surface creators who rank for niche keywords with follower metrics
Competitor analysis — track which videos and creators dominate searches in a product category
Content ideation — analyze hooks, hashtags, and sounds used by top-ranking videos
Social listening — monitor brand mentions and product keywords on a recurring schedule

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":"tiktok-search-scraper","params":{"keywords":["coffee recipes"],"maxItems":5},"maxResults":10}'

Request params

Field	Type	Required	Description
`keywords`	array	required	One or more TikTok search queries — anything you would type into the TikTok search bar (e.g. 'coffee recipes', 'iphone 17 review'). Each keyword returns its top-ranked videos (up to 30 per keyword).
`maxItems`	integer	optional	Maximum total number of videos across all keywords. Set 0 for no limit (up to 30 top-ranked videos per keyword). Capped at 100 per call.

Each result contains

Field	Type	Description
`keyword`	string	Keyword
`position`	integer	Position
`videoId`	string	Video Id
`videoUrl`	string	Video Url
`description`	string	Description
`hashtags`	array	Hashtags
`createdAt`	string	Created At
`createdAtTimestamp`	integer	Created At Timestamp
`duration`	integer	Duration
`coverUrl`	string	Cover Url
`region`	string	Region
`authorId`	string	Author Id
`authorUsername`	string	—
`authorNickname`	string	—
`authorSecUid`	string	—
`authorVerified`	boolean	—
`authorFollowerCount`	integer	—
`authorSignature`	string	—
`likeCount`	integer	—
`commentCount`	integer	—
`shareCount`	integer	—
`playCount`	integer	—
`collectCount`	integer	—
`downloadCount`	integer	—
`repostCount`	integer	—
`musicId`	string	—
`musicTitle`	string	—
`musicAuthor`	string	—
`fetchedAt`	string	—

Use TikTok Search Scraper from Claude, ChatGPT or Cursor

Pick your tool and connect in under a minute. Then just ask — for example: “What are the top 25 TikTok videos for 'protein coffee' this week, and what hooks do they use?”

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":"tiktok-search-scraper","params":{"keywords":["coffee recipes"],"maxItems":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://cool-puffin-608.convex.site/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "tiktok-search-scraper",
        "params": {"keywords":["coffee recipes"],"maxItems":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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