Reddit Comments Search Scraper

Search archived Reddit comments within a subreddit, by author, under a specific post, or under a parent comment. Filter by body text and time range with automatic pagination.

Key Features

• Search comments by body text within a subreddit or scope
• Filter by author, link ID, or parent comment ID
• Support after and before time range filters
• Automatic pagination using the last comment's created timestamp
• Configurable per-request limit (1-100) and total maxItems
• Optional proxy configuration

Input

Field	Type	Required	Description
subreddit	string	No*	Subreddit name without r/
author	string	No*	Filter by username
link_id	string	No*	Post link ID, e.g. t3_1ubt2cm
parent_id	string	No*	Parent comment ID, e.g. t1_abc123
body	string	No	Search comment body (requires one scope field above)
after	string	No	Created after (Unix timestamp or date)
before	string	No	Created before (Unix timestamp or ISO date)
limit	integer	No	Comments per request, 1-100 (default: 100)
sort	string	No	desc or asc (default: desc)
maxItems	integer	No	Max total comments (default: 100)
proxyConfiguration	object	No	Proxy settings

* At least one of subreddit, author, link_id, or parent_id is required.

Input Example

{
    "subreddit": "chatgpt",
    "body": "token",
    "sort": "desc",
    "limit": 10,
    "maxItems": 50
}

Output

Each result includes the full Reddit comment payload plus metadata:

{
	"subreddit": "ChatGPT",
	"all_awardings": [],
	"approved_at_utc": null,
	"approved_by": null,
	"archived": false,
	"associated_award": null,
	"author": "Fit-Yesterday7032",
	"author_flair_background_color": null,
	"author_flair_css_class": null,
	"author_flair_richtext": [],
	"author_flair_template_id": null,
	"author_flair_text": null,
	"author_flair_text_color": null,
	"author_flair_type": "text",
	"author_fullname": "t2_2g1dgyb02p",
	"author_is_blocked": false,
	"author_patreon_flair": false,
	"author_premium": false,
	"awarders": [],
	"banned_at_utc": null,
	"banned_by": null,
	"body": "Semantics\n\nYou're conflating Generative Ai in general and commercial LLMs. One, indeed, only prioritizes that a token is produced; the other doesn't.\n\nWhile LLMs are a type of Generative AI, they are increasingly being designed to be accurate. Through techniques like RLHF (Reinforcement Learning from Human Feedback) and RAG (Retrieval-Augmented Generation), developers ARE trying to make them \"try\" to be accurate.\n\nTo claim that they \"can't fail at doing something they are not even trying to do\" is a semantic technicality. While the base model just predicts text, the product (like ChatGPT or Gemini) is absolutely designed and marketed to provide accurate information. Therefore, when they provide false info, it is a \"mistake\".",
	"can_gild": false,
	"can_mod_post": false,
	"collapsed": false,
	"collapsed_because_crowd_control": null,
	"collapsed_reason": null,
	"collapsed_reason_code": null,
	"comment_type": null,
	"controversiality": 0,
	"created": 1782348795,
	"created_utc": 1782348795,
	"distinguished": null,
	"downs": 0,
	"edited": false,
	"gilded": 0,
	"gildings": {},
	"id": "otmyisp",
	"is_submitter": false,
	"likes": null,
	"link_id": "t3_1qliqds",
	"locked": false,
	"mod_note": null,
	"mod_reason_by": null,
	"mod_reason_title": null,
	"mod_reports": [],
	"name": "t1_otmyisp",
	"no_follow": true,
	"num_reports": null,
	"parent_id": "t1_o1kbd5c",
	"permalink": "/r/ChatGPT/comments/1qliqds/has_anyone_noticed_that_chatgpt_does_not_admit_to/otmyisp/",
	"profile_img": "https://www.redditstatic.com/avatars/defaults/v2/avatar_default_1.png",
	"profile_over_18": false,
	"removal_reason": null,
	"replies": "",
	"report_reasons": null,
	"retrieved_on": 1782348813,
	"saved": false,
	"score": 1,
	"score_hidden": true,
	"send_replies": true,
	"stickied": false,
	"subreddit_id": "t5_7hqomg",
	"subreddit_name_prefixed": "r/ChatGPT",
	"subreddit_type": "public",
	"top_awarded_type": null,
	"total_awards_received": 0,
	"treatment_tags": [],
	"unrepliable_reason": null,
	"ups": 1,
	"user_reports": [],
	"body_html": "<div class=\"md\"><p>Semantics</p>\n\n<p>You&#39;re conflating Generative Ai in general and commercial LLMs. One, indeed, only prioritizes that a token is produced; the other doesn&#39;t.</p>\n\n<p>While LLMs are a type of Generative AI, they are increasingly being designed to be accurate. Through techniques like RLHF (Reinforcement Learning from Human Feedback) and RAG (Retrieval-Augmented Generation), developers ARE trying to make them &quot;try&quot; to be accurate.</p>\n\n<p>To claim that they &quot;can&#39;t fail at doing something they are not even trying to do&quot; is a semantic technicality. While the base model just predicts text, the product (like ChatGPT or Gemini) is absolutely designed and marketed to provide accurate information. Therefore, when they provide false info, it is a &quot;mistake&quot;.</p></div>",
	"scrapedAt": "2026-06-25T02:15:31.707Z"
}

Use Cases

• Subreddit comment monitoring and research
• Keyword tracking in community discussions
• Extracting replies under a specific post or thread
• Author comment history analysis