Reddit Comment Search API: the Camas and Pushshift-Live Alternative (2026)

If you have ever tried to search Reddit for a word inside the comments, not the post titles, and come up empty, you are not doing it wrong. Reddit's official API has no comment-search endpoint. Its search accepts a type=comment mode, but that mode returns the parent posts whose comments matched, never the comment text itself. The tools that used to fill this gap, Camas and the Pushshift archive behind it, went dark for the public in 2023. This guide explains exactly why comment search is missing, what replaced Pushshift, and how to search Reddit comment bodies by keyword over a plain REST call in 2026.

Not affiliated with Reddit Inc. redditapis.com is an independent, third-party REST layer built on Reddit's official API.

Last updated 2026-08-02.

TL;DR: Reddit's own API cannot return comment bodies from a search. The type=comment parameter matches comment text but hands back the parent posts, so you get threads with no comment text. Camas and Pushshift, the old public comment-search stack, closed to non-moderators in 2023. In 2026 you have three paths: PullPush (a free historical archive with a /reddit/search/comment endpoint and no reliability promise), a do-it-yourself pass on Reddit's API (search for matching posts, fetch each comment tree, filter the bodies), or a managed REST API that does that step for you with /search/comments/deep and returns the actual matching comments with body, score, author, and permalink. Use /signup to test the endpoints or read the pricing guide.

• Reddit's type=comment search returns parent posts, not comment bodies
• Camas and Pushshift, the old comment-search stack, closed to the public in 2023
• PullPush is the free historical archive; a managed API is the live-search path
• /search/comments finds the threads; /search/comments/deep returns the comments

Is there a Reddit comment search API in 2026?

There is no comment-search endpoint in Reddit's official API. Reddit exposes post search, subreddit search, and user search through its documented search endpoint, and that route accepts a type=comment value, but that value is a matching mode rather than a result type. Reddit matches your keyword against comment text and then returns the posts those comments belong to, so you can find that a discussion mentioned your term, but you cannot read the comment that mentioned it. This is the single most confusing thing about Reddit search, and it is why the question keeps resurfacing in the developer community.

The gap is not theoretical. Developers hit it constantly and land in the same place, asking where the comment-search endpoint went after Pushshift closed.

r/

r/redditdev·u/Green_Team_4585

Is comment search supported API? I can't find the endpoint

00

Open on Reddit

The three ways to search Reddit split cleanly by what they return, and only one of them gives you comment text.

The practical takeaway is that "search Reddit comments" is really two jobs. Finding the threads where a term comes up is one job, and Reddit's own comment-search mode does that, as does our /search/comments endpoint. Reading the comments that matched is a separate job that Reddit's API never finishes for you. The rest of this guide is about closing that second gap, and about the history that opened it.

Why comment search disappeared: Camas, Pushshift, and 2023

Comment search used to be easy, and then it was not. For years, Pushshift maintained a full-history archive of Reddit posts and comments, and Camas was a fast search UI built on top of it that let anyone search comment text, filter by author, and scope to a subreddit. In 2023, Reddit's Data API changes cut Pushshift off from the public, restricting it to verified moderators, and Camas lost the data source it depended on. Overnight, the most common way to search Reddit comments simply stopped working, and the official API had no equivalent to replace it.

The shutdown removed a specific stack of capabilities at once.

• Pushshift: the full-history archive of posts and comments, closed to the public and restricted to verified moderators
• Camas: the fast comment-search UI that read from Pushshift, left with no data source to query
• The gap: Reddit's own Data API still exposes no comment-search endpoint to replace either

The reaction in the developer community was immediate, and it has not really stopped since. The recurring thread is someone with a legitimate need looking for comment search after the archive closed.

r/

r/redditdev·u/atw9x

Searching for comments after PushShift

00

Open on Reddit

Part of why this hurt is that Reddit comment data turned out to be quietly valuable, especially for AI. Pushshift's archive had become a standard corpus for training and research, which is part of why access tightened in the first place.

kalomaze

@kalomaze

while this is funny to say for the meme i think you guys fail to realize just how barren/absent natural conversation would be in the data w/o reddit in pretraining one of the smartest things Mistral pretraining team did was stockpiling the pushshift api data

The API changes touched a whole cluster of tools at once, and the community kept a running map of which parts of the ecosystem were affected and where the surviving pieces, including the Pushshift community, had moved.

Fed 🐻

@foliofed

Subreddits to watch regarding the Reddit API drama r/reddit - official announcements from Reddit r/redditdev - sub for 3rd party developers r/Save3rdPartyApps - sub organizing protest r/apolloapp - sub for Apollo (RIP) r/ModCoord - angry moderators coodinating r/pushshift -

There is a reasonable argument, made loudly at the time, that relying on a single volunteer-run archive for critical infrastructure was always fragile. That view has merit. But it does not change the practical problem a developer faces today: the convenient comment search is gone, and you need a path that works now. The death of the free JSON endpoint is a related chapter of the same story.

Why Reddit's own search returns posts, not comments

When you add type=comment to a Reddit search request, Reddit does match your keyword against comment bodies, but the objects it returns are posts. A post object carries a title, selftext, score, and comment count, so the fields that populate look reasonable, which is exactly why the behavior is so easy to miss. What you never get back is the comment that matched, its text, or which comment it even was. Reddit does not expose that in the search response, so inventing a field for it is not an option.

Developers discover this the hard way, usually after appending the parameter and getting the same title-only results they got without it.

You can see the exact behavior by calling the parent-posts endpoint, which mirrors Reddit's own comment-search mode. A first-party call to GET /api/reddit/search/comments?q=pushshift&limit=5 on 2026-08-02 returned a comments key whose values were posts, each carrying id, title, author, subreddit, upvotes, num_comments, selftext, url, link_url, and created, with an after cursor that was a t3_ post fullname. The response key is named comments for backward compatibility, but every value is a post. There is no body, no comment permalink, and no marker of which comment triggered the match.

That is the whole reason a dedicated comment-search step exists: to take those matching posts and actually pull the comments out of them. Reddit's search API stops one step short of the data most people searching comments actually want.

The two comment-search endpoints: parent posts vs real bodies

Because "search comments" is two jobs, a comment-search API is cleanest when it exposes two endpoints. The first, /search/comments, does exactly what Reddit's own mode does: it returns the parent posts whose comments matched, at the standard single-read price, which is ideal when you only need to find the threads. The second, /search/comments/deep, finishes the job: it expands each matching post's comment tree and returns the actual matching comment bodies. The split lets you pay for depth only when you need it.

Seen side by side, the difference between the two is the difference between a lead and the answer.

The comparison is easiest to hold as a small table:

	/search/comments	/search/comments/deep
Returns	Parent posts (t3)	Matching comment bodies (t1)
Comment text	No	Yes
Per-result fields	title, score, num_comments	body, score, author, permalink, parent_post
Cost tier	Standard read (~$0.002)	Premium read (~$0.02)
Best for	Finding threads	Reading the comments

The reason the deep endpoint costs more is not arbitrary: one call to it fans out into a comment-search read plus one comment-tree fetch per expanded post, so it is doing several reads on your behalf. You are paying to skip writing and maintaining that fan-out yourself. If you only need to know which threads mention a term, the cheaper parent-posts call is the right tool, and it pairs naturally with the comments endpoint when you want to pull a specific thread in full.

How to search Reddit comments by keyword

To search Reddit comment bodies by keyword with a managed API, you send one authenticated request to the deep endpoint and read the comments back. There is no OAuth app to register, no comment tree to walk, and no filtering loop to write: the endpoint matches your query against the visible comment text at word boundaries, so a hit is always a real mention a reader would see, not a substring inside a link. Here is the call in curl, using your API key in place of the placeholder:

curl -s "https://api.redditapis.com/api/reddit/search/comments/deep?q=pushshift%20alternative&limit=10&sort=top" \
  -H "Authorization: Bearer YOUR_API_KEY"

The same call in Python, printing each matching comment with its score and subreddit:

import requests

API_KEY = "YOUR_API_KEY"

resp = requests.get(
    "https://api.redditapis.com/api/reddit/search/comments/deep",
    headers={"Authorization": f"Bearer {API_KEY}"},
    params={"q": "pushshift alternative", "limit": 10, "sort": "top"},
    timeout=30,
)
resp.raise_for_status()
data = resp.json()

for c in data["comments"]:
    print(f"[{c['score']:>4}] r/{c['subreddit']}  u/{c['author']}")
    print(f"       {c['body'][:120]}")
    print(f"       {c['permalink']}")

print("meta:", data["meta"])

Run against the live API on 2026-08-02, that query scanned 10 parent posts and returned the matching comments, including a 319-score comment in r/DataHoarder arguing that Pushshift's shutdown was overdue. The meta block reported posts_scanned, comments_matched, comments_returned, and a truncated flag, so you always know whether a comment tree was too deep to fully expand. A short walkthrough of the broader no-code and low-code approaches to pulling Reddit data, for readers who prefer a visual, is here:

If you want to scope the search, the same Reddit query operators work: subreddit:webdev keyword limits the match to one community, author:name keyword scopes to a person, and "exact phrase" matches a phrase. The advanced search filters guide covers the full operator set.

How deep comment search actually works under the hood

The deep endpoint is not magic; it automates the exact do-it-yourself pipeline a developer would otherwise build by hand with a wrapper like PRAW. It starts from Reddit's own comment-search mode to get the matching parent posts, then fetches each post's comment tree with bounded concurrency, walks the nested replies, and keeps only the comments whose visible text matches your query. Understanding the steps matters because they explain both the cost and the honest limits: every stage is a real Reddit read, and a tree deep enough to be truncated can drop a match.

Laid out as a pipeline, the four stages make the tradeoffs visible.

Two design choices are worth calling out. First, limit bounds the number of parent posts expanded, not the number of comments returned, because each parent post is one more upstream fetch and that is where cost and latency come from. Second, the endpoint reports honest meta: it tells you how many posts it scanned, how many comments matched, how many it returned, whether a cap trimmed the list, and whether any tree was truncated. A first-party probe on 2026-08-02 made this concrete.

That transparency is the difference between a best-effort search you can trust and one that silently lies about completeness. Because the pipeline reads Reddit's live data, it reflects the present rather than a frozen archive, which is exactly the tradeoff the next section unpacks. For high-volume pulls, the same pattern underpins Reddit as a RAG data source.

The research mode: who is talking about your keyword

Sometimes the useful answer is not the comments but the people. The deep endpoint's group_by=author mode inverts a keyword search: instead of a flat list of matching comments, it returns the distinct authors who mentioned your query, ranked by how many of their comments matched and then by total score. Each author comes back with a comment count, a total score, the subreddits they matched in, and their single top comment. That is the shape you want for finding advocates, detractors, or domain experts on a topic, rather than just the raw mentions.

The call is the same endpoint with one added parameter and an optional cap on how many people come back.

import requests

API_KEY = "YOUR_API_KEY"

resp = requests.get(
    "https://api.redditapis.com/api/reddit/search/comments/deep",
    headers={"Authorization": f"Bearer {API_KEY}"},
    params={"q": "rate limit", "group_by": "author", "limit": 10, "max_authors": 5},
    timeout=30,
)
resp.raise_for_status()
data = resp.json()

for a in data["authors"]:
    subs = ", ".join(a["subreddits"])
    print(f"u/{a['author']}  ({a['comment_count']} comments, score {a['total_score']}) in {subs}")

print("meta:", data["meta"])

Run on 2026-08-02, a group_by=author search for "rate limit" scanned ten posts, found eighteen matching comments, and resolved them to seventeen distinct authors, capped to the five most prolific by the max_authors parameter. The meta block reported authors_matched, authors_returned, and authors_capped, so a trimmed people-list is never read as the whole set.

Removed accounts are dropped in this mode, because Reddit collapses every deleted user to the same [deleted] string, which would otherwise merge unrelated people into one phantom author. This is the mode most teams reach for when the goal is lead detection or influencer mapping rather than a raw comment feed.

PullPush vs a live comment-search API

The most important choice is between a historical archive and live search, because they solve genuinely different problems. PullPush is the community successor to Pushshift: a free, donation-funded archive that stores a large corpus of past comments and exposes a /reddit/search/comment endpoint to query them. It is the right tool when you need years of history on a term. A managed live API, by contrast, searches Reddit's current data through official access, so it reflects what is on Reddit now and carries a documented rate budget and a stable response shape. Neither is strictly better; they sit at opposite ends of the time axis.

The tradeoff is clearest as a direct comparison of what each is built to do, laid out side by side across data source, freshness, reliability, cost, and fit.

The honest recommendation is to match the tool to the time horizon. If you are studying how a topic was discussed over the last five years, PullPush and its free archive are hard to beat, and our Pushshift alternatives roundup scores the archive options in detail. If you are monitoring a keyword for fresh mentions, powering a product feature, or need a reliability promise a volunteer archive cannot make, a managed live API is the fit, and it will not 403 your cloud host the way the raw Reddit paths increasingly do.

The comment-search response, field by field

A comment-search API is only as useful as the fields it returns, and the deep endpoint returns a complete, structured comment object rather than presentation HTML. Every matching comment comes back with the data you need to rank it, attribute it, and link to it, plus a compact reference to the post it lives under. Knowing the exact shape upfront saves you from probing the response by trial and error.

The deep comment-search response returns these fields per comment.

Alongside the comments array, the response carries an after cursor for pagination and the meta block that reports posts_scanned, comments_matched, comments_returned, capped, and truncated. In group_by=author mode the array becomes authors and each entry carries author, comment_count, total_score, subreddits, and top_comment. Because everything arrives as clean JSON rather than escaped markup, you can drop it straight into a pipeline without an HTML-stripping step, unlike the RSS feed path which returns presentation markup. The exact schemas live in the full API documentation.

How far back you can search, and how to paginate

Live comment search reads Reddit's current, reachable data rather than a full historical dump, so its depth is bounded and best-effort by design. A single call expands a limited number of matching parent posts, and a comment that was deleted since Reddit indexed it, or one nested below the fetched tree depth, will not appear, which the truncated flag warns you about. This is not a defect so much as the nature of reading the present: the archive job and the live-search job are different, and mixing them up is the most common source of surprise.

To widen a search beyond one call, you paginate.

The response after value is Reddit's post-search cursor, so passing it back as after= expands the next batch of parent posts, and each page stays bounded in cost and latency. That lets a caller walk as far as they want without any single call ballooning. If your real need is years of history on a term rather than a wide sweep of the present, that is the point at which a historical archive is the better instrument, because it stores the past instead of reading the current listing. The mechanics of the cursor are the same across the API, and the pagination guide covers them in full, including how the cursor interacts with rate limits.

What comment search costs, and its honest limits

Comment search on a managed API is priced by how much work each call does, and the deep endpoint is honest about being a premium operation. A standard single read, including the /search/comments parent-posts call, runs around $0.002. The deep call runs around $0.02 because it performs a comment-search read plus one comment-tree fetch per expanded post, so a limit=10 deep call is roughly ten reads bundled into one request and one response. Framing it that way makes the price make sense: you are buying a fan-out you would otherwise build and pay to run yourself.

The cost is only half the picture; the limits matter just as much.

The honest limits are worth stating plainly. Deep search is best-effort, not exhaustive: it will miss a comment deleted after indexing or one below the fetched depth. It reads live data, so it is not a substitute for a full historical archive, a distinction Reddit draws in its own Data API Wiki. And the premium price means you should reach for the cheaper parent-posts call whenever you only need to find threads, not read every comment. None of this is hidden, because the meta block reports exactly what was scanned and returned. For a full cost breakdown against running your own access, see the pricing guide and the pricing versus general scraping platforms comparison.

What builders do with Reddit comment search

Comment search is not an academic feature; it powers a specific set of real builds that post-title search cannot serve. The common thread is that the signal lives in the replies, not the headlines: the buying intent, the product complaint, the recommendation, and the expert answer are all in the comments. Being able to search comment bodies by keyword, and to invert that into who is saying it, turns Reddit from a set of threads into a queryable opinion layer.

The recurring use cases cluster into a handful of patterns, each one a job that lives in the replies rather than the post titles.

• Brand and product monitoring: watch comments for a product or competitor name and surface fresh mentions
• Lead detection: catch the buying-intent phrasing that shows up in replies, not headlines
• Market and sentiment research: treat scored comments as a live survey of opinion
• Expert mapping: find who talks about a topic through the author-grouping mode
• AI context: feed structured comments into an agent or a retrieval pipeline

Brand monitoring watches for a product or competitor name in comments and surfaces fresh mentions to a human. Lead detection scans niche communities for the buying-intent phrasing that shows up in replies rather than post titles. Market and sentiment research treats the comment corpus as a survey of what people actually think, ranked by score. Author-mode research maps the experts and advocates on a topic. And AI builds feed structured comment context into an agent or a retrieval pipeline, because a model reasoning about a topic needs the discussion, not just the headline. Each of these is a comment-search problem first, and a good reason the missing endpoint has been felt so widely.

When you need something else, and the next step

Comment search covers a lot, but it is not the answer to every Reddit-data question, and being honest about the boundaries saves you from forcing the wrong tool. If you need years of historical comments on a term, a free archive like PullPush is the better fit than live search. If you already know the exact post and want its full discussion, the comments endpoint fetches the whole tree by permalink without a search step. If you want to search post titles and bodies rather than comments, that is post search. And if you want to write a reply rather than read one, that is a write endpoint, not a search one. Matching the job to the tool is most of the battle, and finding the right subreddits first makes every one of them sharper.

For the job this guide is about, searching Reddit comment bodies by keyword over live data, a managed REST API is the path that works in 2026 without rebuilding what Camas and Pushshift used to do.

• Read the Reddit data API guide for the full access picture
• Compare the paths in dollars in the pricing guide
• Get an API key to test /search/comments/deep directly, with free credit at signup

Need to search Reddit comments, not just posts? redditapis.com gives you live comment search behind one bearer token: /search/comments to find the threads, /search/comments/deep for the actual comment bodies, and a group_by=author mode for who is talking. See pricing or get an API key with free credit at signup to pull the comments Reddit's own search leaves out.