TikTok Comments Scraper

TikTok

Operated by Sourcelane✓ verified

Scrapes comment threads from TikTok videos, extracting comment text, author identifiers and display names, engagement metrics (like counts and reply counts), full nested reply threads per top-level comment, and timestamps in ISO 8601 and Unix epoch formats. Produces structured records that combine each top-level comment with its nested replies; supports including or excluding replies and controlling reply depth. Core mechanism fetches comment data from TikTok endpoints and returns structured metadata useful for text analysis, moderation, engagement measurement, and researcher workflows.

Verified Sep 28, 3:55 AM

$0.002

per comment

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

What people use it for

Sentiment analysis and brand monitoring on TikTok content
Competitive research to evaluate audience responses to competitor videos
Influencer vetting to assess comment quality and engagement authenticity
Content research to identify recurring questions or pain points in comment sections
Academic research on social media behaviour

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":"tiktok-comments-scraper","params":{"videoUrl":"https://www.tiktok.com/@australia/video/7632203705881824520","maxComments":5},"maxResults":10}'

Request params

Field	Type	Required	Description
`videoUrl`	string	required	Full TikTok video URL, e.g. https://www.tiktok.com/@username/video/1234567890123456789
`maxComments`	integer	optional	Maximum number of top-level comments to scrape. Capped at 100 per call.
`includeReplies`	boolean	optional	Fetch replies for each comment and nest them in the output record.
`maxRepliesPerComment`	integer	optional	Maximum replies to fetch per comment. Only used when Include Replies is enabled.

Each result contains

Field	Type	Description
`videoId`	string	Video Id
`commentId`	string	Comment Id
`text`	string	Text
`authorUsername`	string	Author Username
`authorNickname`	string	Author Nickname
`authorSecUid`	string	Author Sec Uid
`likeCount`	integer	Like Count
`replyCount`	integer	Reply Count
`createdAt`	string	Created At
`createdAtTimestamp`	integer	Created At Timestamp
`replies`	array	—

Use TikTok Comments 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://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":"tiktok-comments-scraper","params":{"videoUrl":"https://www.tiktok.com/@australia/video/7632203705881824520","maxComments":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": "tiktok-comments-scraper",
        "params": {"videoUrl":"https://www.tiktok.com/@australia/video/7632203705881824520","maxComments":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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