Reddit Search Scraper & API: Posts & Comments by Keyword

Reddit Search Scraper: Posts & Comments by Keyword

Type keywords and get the Reddit posts (or comments) that match them, site-wide or inside one subreddit: title, text, score, upvote ratio, comments count, author, flair, media and date, and the post's comment tree if you want it. No login, no cookies, no API key. Export as JSON, CSV or Excel, or read it through the Apify API.

• Search that contains your words: Reddit's search returns loosely related posts (for "home assistant", 17 of the top 100 contain it). Turn on strict search and only posts with all the words of your query, as whole words, are kept; the others are not charged.
• Comment search: comments that contain your keywords, anywhere on Reddit or in one subreddit, each with its post's title and URL.
• Comment trees on demand: each post found can come with its comments, each with parentId and depth.
• Only new results on a schedule: turn on Only new since the last run and each run returns and charges only what earlier runs did not return.

$2.50 per 1,000 posts, $2.50 per 1,000 comments, less on paid plans, plus $0.005 per run. Searches that fail, duplicates and posts removed by your filters are not charged.

Optional AI analysis of each post and comment (sentiment, intent, entities, summary, pain point, business signals, your own labels): $0.50 per 1,000 analyzed records.

Quick start

1. Type keywords into Search queries (posts) or Comment search (comments), one search per line. Quotes keep a phrase together: "home assistant".
2. Optionally name a subreddit in Search only inside this subreddit, choose a sort and a time range.
3. Click Start and read the results in the run's Output tab.

Through the API:

{
  "searchQueries": ["home assistant dashboard"],
  "searchSubreddit": "homeassistant",
  "strictSearch": true,
  "searchSort": "top",
  "timeFilter": "month",
  "maxPostsPerSource": 100
}

Comments that name a product, each week, only the new ones:

{ "commentSearchQueries": ["\"apify\""], "searchSort": "new", "onlyNew": true, "watchName": "apify-mentions" }

Like any Apify Actor, it can be scheduled, connected to webhooks, Make, Zapier, n8n, or called by AI agents through Apify's MCP server.

Output

One record per post (or comment). A real search result (October 11, 2026, author replaced, some fields left out):

{
  "type": "post",
  "id": "1wpy5q6",
  "url": "https://www.reddit.com/r/homeassistant/comments/1wpy5q6/claude_and_home_assistant/",
  "subreddit": "homeassistant",
  "title": "Claude and Home Assistant",
  "body": "When I bought my house about 3 years ago one of the first things I did was start down the home automation path. …",
  "author": "example_user",
  "createdAt": "2026-09-25T14:42:18Z",
  "score": 157,
  "upvoteRatio": 0.74,
  "numComments": 283,
  "flair": "💬 Discussion",
  "mediaType": "text",
  "source": "search: home assistant",
  "scrapedAt": "2026-10-11T18:53:41Z"
}

Field	What it holds
title, body, flair	the post as written, and its flair
score, upvoteRatio, numComments	the counters Reddit shows
scorePerHour, commentsPerHour	how fast the post grew since it went up
mediaType, imageUrls, videoUrl, link	text, image, gallery, video or link, and the media links
source	the search that found the post

A comment record has body, score, createdAt, postId, postTitle and parentId. Comments read from a post's tree also have their depth and rootCommentId; for a comment found by comment search, Reddit does not give its place in the thread, so both are null. Field names stay the same between runs: a value Reddit does not provide is null, not missing. The run summary is the OUTPUT record of the run's key-value store.

AI analysis (optional)

Turn on AI analysis and every post and comment gets an aiAnalysis object next to its own fields: $0.50 per 1,000 analyzed records, every field and signal included. A real result (post "Best and inexpensive CRM for small businesses" in r/CRM, analyzed October 14, 2026, with two labels of our own; some entities left out):

"aiAnalysis": {
  "language": "en",
  "sentiment": "mixed",
  "sentimentScore": -0.2,
  "emotion": "anticipation",
  "intent": "seeking_recommendation",
  "category": "software",
  "topics": ["crm alternatives", "hubspot pricing", "small business software"],
  "entities": [{"name": "HubSpot", "type": "brand"}, {"name": "Zoho", "type": "brand"}, {"name": "Pipedrive", "type": "brand"}],
  "summary": "A user seeks a cheaper CRM alternative to HubSpot that retains key features like lead tracking and reporting for their small businesses.",
  "painPoint": "HubSpot is becoming too expensive",
  "wantsHelp": true,
  "buyingSignal": true,
  "mentionsPrice": true,
  "featureRequest": false,
  "isVendor": false,
  "relevance": 1.0,
  "labels": {"switching": true, "budget": true}
}

Field	What it holds
sentiment, sentimentScore	positive, negative, neutral or mixed, and a score from -1 to 1
emotion	the main emotion (joy, frustration, anger, curiosity, confusion, none…)
intent	what the author wants: question, seeking_recommendation, complaint, praise, purchase_intent, comparison, announcement, self_promotion, discussion, humor
category, topics, entities	a category, up to 3 topics, and the brands, products, companies, people and places named
summary, painPoint	one English sentence, and the problem or frustration the author expresses (or null)
wantsHelp, buyingSignal, mentionsPrice, featureRequest, isVendor	business signals, true or false: asks for help, ready to buy or pay, names a price or budget, asks for a feature, sells or builds what they talk about
relevance	how much the record is really about your search, 0 to 1
labels	your own yes/no labels

Your own labels: up to 5, as {"label_name": "what makes it true"}, for example {"switching": "The author wants to switch from one product to another"}. Included in the price.

• Charged once per record analyzed in full. Deleted, removed, bot (AutoModerator) and empty records are not analyzed and not charged. If an analysis fails, the record is still delivered (and charged as usual), its aiAnalysisStatus is failed with the reason in aiAnalysisError, and the analysis is not charged.
• Any language in, summaries in English. The first ~2,500 characters of a very long text are analyzed.
• Works with the one-record-per-item output format (not the Markdown thread format).
• It adds time: about a minute and a half per 100 records.

Inputs

• Search queries: keywords as typed in Reddit's search box. Comment search: keywords to find in comments.
• Search only inside this subreddit: one subreddit, or empty for all of Reddit.
• Strict search (exact words only), and where the words must appear (title or text, or title only).
• Max results per search (Reddit lists about 250 per search) and Max results in total.
• Search sort (relevance, hot, top, new, most comments) and Time range.
• Filters: dates, NSFW, excluded keywords, post types, flairs. Removed posts are not charged.
• Comments: include the comments of each post found, how many, how deep, in which order.
• AI analysis and Your own labels: the optional analysis described above.
• Output format: one record per item, or each thread as one Markdown record for LLMs.
• Only new since the last run and Watch name, for scheduled runs.

Pricing

Pay per event:

Apify plan	Posts	Comments
Free	$2.50 / 1,000	$2.50 / 1,000
Starter	$2.40 / 1,000	$2.40 / 1,000
Scale	$2.30 / 1,000	$2.30 / 1,000
Business and above	$2.20 / 1,000	$2.20 / 1,000

AI analysis (optional): $0.50 / 1,000 analyzed records on every plan.

Plus the start: $0.005 per GB of run memory. Not charged: searches that fail, error records, duplicates, posts removed by a filter or by strict search, results already returned to a watch. Set Maximum cost per run in the run options and the run stops before going over it.

Run it in production

Keep one saved input and let Apify run it on a schedule.

1. In Apify Console open Schedules and create a schedule with a cron time (0 6 * * * is every day at 06:00 UTC, 0 6 * * 1 every Monday).
2. Add this Actor with your input. Turn on Only new since the last run and give a Watch name: runs with the same name share one memory, so you can add or remove a source later without getting old results again. Without a watch name, changing the input starts a new memory and returns everything again.
3. With Only new, Max results per search is the window watched: keep it above the number of new results you expect between two runs. Without Only new, set Posted after to the length of your rhythm (1 day for a daily run, 7 days for a weekly one) and remove the overlap on id in your own storage.

What it costs per month (Free plan prices; Business prices in brackets). Each run costs its start ($0.005) plus the posts or comments it returns. With Only new since the last run, only new ones are returned and charged, so the cost follows how much new content there is:

Schedule	New posts or comments per month	Cost per month
Daily (30 runs)	1,000	$2.65 ($2.35)
Daily (30 runs)	10,000	$25.15 ($22.15)
Weekly (4 runs)	1,000	$2.52 ($2.22)

Optional AI analysis adds $0.50 per 1,000 records analyzed. Set Maximum cost per run so that a run never goes over what you planned.

Call it from code. Start a run and wait for the results in one request (this call waits up to 300 seconds, so use it for small jobs):

curl -X POST "https://api.apify.com/v2/acts/quarra~reddit-search-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"commentSearchQueries": ["\"acme crm\""], "searchQueries": ["\"acme crm\""], "strictSearch": true, "searchSort": "new", "maxPostsPerSource": 100, "onlyNew": true, "watchName": "acme-mentions"}'

For bigger jobs, start the run, wait for it to end, then read its dataset:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("quarra/reddit-search-scraper").call(run_input={"commentSearchQueries": ["\"acme crm\""], "searchQueries": ["\"acme crm\""], "strictSearch": True, "searchSort": "new", "maxPostsPerSource": 100, "onlyNew": True, "watchName": "acme-mentions"})
items = list(client.dataset(run["defaultDatasetId"]).iterate_items())

Connect it. Add a webhook on the event ACTOR.RUN.SUCCEEDED (Console, Integrations tab) to be called when a run ends, then read the dataset of that run. Make, Zapier and n8n have Apify modules: run the Actor, get the dataset items, then send each one to Slack, Google Sheets, Airtable or your CRM. AI agents can call the Actor through Apify's MCP server.

Send results to Slack, Notion or Discord

Pick one of your Apify MCP connectors in "Send results to your app" (Notion connects in one click), or paste a Slack, Discord, Make, Zapier or n8n webhook URL. After each successful run, a summary lands there: the number of results, the first 25 with their links, and a link to the full dataset. Schedule the Actor with "Only new since the last run (monitoring)" turned on and new results reach your team every day without opening Apify.

Limits

• Reddit lists about 250 posts per search. Go beyond Reddit's listing cap combines sorts and time ranges to get more; use the date filters for a precise window.
• Strict search checks words, not relevance; quotes around a phrase fix most false matches.
• Quarantined communities are visible to logged-in accounts only. The Actor reports them and does not log in.

FAQ

Do I need a Reddit account or API key? No account, no cookies, no API key. Platform costs are included in the price.

Why did my run return nothing? The status message, the free error records and the OUTPUT record give the reason for each search: no result, nothing in your date window, nothing matching strict search. Such a run costs only the start.

Is it legal? It collects public posts and comments any logged-out visitor can see. Reddit's terms and privacy law (GDPR in the EU) apply to how you use the data.

Does the Actor send anything to Quarra? Only when a run fails or runs out of time: the Actor, its build, the error type, the line of our code where it happened, and the memory and time the run was given, so we can fix it fast. Never your input, your results, your account or the run ID.

Related Actors

• Reddit Scraper: subreddits, searches, post URLs and users in one Actor.
• Reddit Comments Search Scraper: comments by keyword.
• Reddit Comments Scraper: all the comments of posts from their links.
• Reddit Subreddit Scraper: the posts of any subreddit.
• Reddit Post Scraper: posts from their links, or refreshed by ID to follow their score.
• Reddit Lead Finder: the posts and comments where people ask for a recommendation or show buying intent.