Issue Comments Data API
Scrape GitHub Issue Comments data with one API call. Returns comments under `data.items[]` — each entry includes `id`, `user.login`, `body`, `reactions.total_count`, and `created_at`. Pass either an `/issues/N` or `/pull/N` URL; both resolve to the same comment thread on GitHub's API.
Try the GitHub Issue Comments API
See real data before writing a single line
Searching 27 platforms in parallel
What can you do with the Issue Comments API?
The Issue Comments endpoint gives you structured GitHub data with computed fields in a single request. No scraping infrastructure to build or maintain.
Example Request
GET /v1/github/issue/comments?url=https%3A%2F%2Fgithub.com%2Ffacebook%2Freact%2Fissues%2F27522Parameters
| Parameter | Required | Description |
|---|---|---|
| url | Yes | GitHub HTML URL of the issue or PR. |
| sort | No | `created` or `updated`. Defaults to `created`. (created | updated) |
| direction | No | `asc` or `desc`. Defaults to `asc`. (asc | desc) |
| since | No | Only comments updated at or after this ISO 8601 timestamp. |
| per_page | No | Comments per page (1–100). Defaults to 30. |
| page | No | 1-indexed page number. |
How does the GitHub Issue Comments API work?
Send a GET request with your API key and get back clean, structured JSON. Every response follows our unified schema with computed fields.
Method
GET
Response
JSON
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Computed fields, not just scraped
Every response includes engagement_rate, estimated_reach, content_category, and language — ready to use.
No code required
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import requests
response = requests.get(
'https://www.socialcrawl.dev/v1/tiktok/profile',
params={'handle': 'charlidamelio'},
headers={'x-api-key': 'sc_YOUR_API_KEY'}
)
data = response.json(){
"success": true,
"platform": "tiktok",
"data": {
"author": { "username": "charlidamelio", "followers": 124000 },
"engagement": { "likes": 5200, "engagement_rate": 0.045 },
"metadata": { "language": "en", "content_category": "food" }
}
}Ready to scrape GitHub Issue Comments data?
Get your API key and start pulling GitHub data in under 60 seconds.
