fetchlayer.dev Sign in Reddit data.
Without the scraping.
Posts, comments, subreddits, and user profiles — fetched live, returned as clean JSON via REST or MCP. No scraper to maintain, no rate limits to manage.
Read our field report: Reddit's API is officially dead in 2026.
Trusted by developers shipping real products.
270,375 served today
Request
$ curl -X POST api.fetchlayer.dev/reddit/search \ -H "Authorization: Bearer ss-..." \ -d '{"query": "best CRM", "sort": "top"}'
Response
{
"results": [{
"title": "What CRM do you hate?",
"subreddit": "sales",
"score": 184,
"numComments": 67
}]
} What you get
Every public Reddit endpoint, structured.
We access publicly available Reddit data and return it as clean, typed JSON. No authentication with Reddit required on your end.
Search posts
Full-text search across all of Reddit or scoped to a subreddit. Sort by relevance, hot, new, or top.
Scrape comments
Full comment trees with scores, authors, timestamps, and nested replies. Paginate deep threads.
Subreddit scraper
Posts, metadata, subscriber counts, rules — scrape any public subreddit. Sort by hot, new, top, rising.
User profiles
Karma, bio, account age, post history, comment history for any public user.
Trending & popular
r/popular feed and community leaderboards. See what's trending right now.
MCP for AI agents
Connect your AI IDE to Reddit data with one config block. Works with Cursor, Windsurf, Claude.
API reference
One base URL. Fifteen endpoints.
All public data. POST with JSON body, get JSON back. Auth via Bearer token.
Endpoint
What it returns
Category
search Posts matching a keyword — globally or within a subreddit
Searchsearch-comments Comments matching a keyword — globally or within a subreddit
Searchpost Full post body + entire comment tree (paginated)
Contentcommunity-posts Posts from any subreddit — hot, new, top, rising, controversial
Communitycommunity-details Subreddit metadata — subscribers, description, rules
Communityuser-profile Karma, bio, account age, and public info
Useruser-posts All posts submitted by a user
Useruser-comments Comment history for any public user
Usersearch-communities Find subreddits by keyword
Searchsearch-users Find Reddit users by name
Searchcomment-permalink Single comment with its parent context and replies
Contentpopular r/popular — what's trending across Reddit right now
Discoverleaderboard Trending communities leaderboard
Discoverresolve-url-type Detect what a Reddit URL points to (post, comment, user, sub)
Utilityexplore Discover communities grouped by topic
DiscoverBase: POST /api/reddit/{endpoint} · All params optional except where noted · Pagination via pages param
TypeScript / JavaScript? Use the open-source SDK: @fetchlayer/reddit on npm · Source on GitHub
MCP & agents
Your AI already knows
how to use this.
One config block and every Reddit endpoint becomes a first-class tool inside your agent. No SDK, no wrapper code, no glue logic — just paste and go.
{
"mcpServers": {
"fetchlayer": {
"url": "https://mcp.fetchlayer.dev",
"headers": {
"Authorization": "Bearer sk-..."
}
}
}
} Works in Cursor, VS Code, Windsurf, Claude Desktop and any MCP host.
Find what people are saying about "Tailwind vs Bootstrap" on Reddit, get the top 5 posts this month.
↳ calling fetchlayer.reddit.search
{"q": "Tailwind vs Bootstrap", "limit": 5, "sort": "top"}
Found 5 posts. The most discussed is "Why I switched back to Tailwind" with 342 comments in r/webdev. Sentiment is mixed — Tailwind wins for speed, Bootstrap wins for teams.
Works with every MCP-compatible tool
API examples
Request in, structured JSON out.
Pick an example, hit Run, and see the response. Every endpoint works the same way.
Examples
Request
POST /api/reddit/search { "query": "CRM pricing complaints", "sort": "top", "limit": 10 }
Response
200 OK · 1.2s{
"results": [
{
"title": "What CRM do you hate and why?",
"subreddit": "sales",
"score": 184,
"numComments": 67,
"url": "https://reddit.com/r/sales/comments/..."
}
]
} Use cases
What developers build with Reddit data.
Same API, endless applications. Here's what teams ship with our endpoints.
Competitor intelligence
Search public forums for any brand or product. Get unfiltered opinions, complaints, and praise from real users.
AI agent context
Feed real user conversations straight into your LLM pipeline. Structured data, zero parsing scripts.
Brand monitoring
New posts, new mentions, new complaints. Sort by recency and run it on a schedule.
Product research
Pull customer pain points from niche communities. Real people, real frustrations, no surveys.
Content pipelines
Trending discussions become blog ideas, newsletters, social content. Automate your content sourcing.
Lead generation
Find people asking for solutions you sell. Identify intent signals in the right communities.
Instant research. Zero setup.
You can use FetchLayer with AI coding agents like OpenAI Codex, Claude Code, Cursor, or Windsurf via MCP. But if you just want results now — no IDE, no code, no terminal — open FetchLayer Research Chat and describe what you need.
Found 47 leads across 12 subreddits matching your criteria. Exporting now...
leads-saas-crm-2026-06.csv
47 rows · 6 columns · ready to download
Via AI Coding Agents
Connect via MCP and let your AI agent call FetchLayer tools inline. Fully customizable — build pipelines, chain tools, add your own logic. The most powerful option for devs who need total control over their workflow.
- Best for: custom pipelines & automated workflows
- Fully programmable — chain any tools together
- Setup: add MCP config to your AI IDE
- Output: inline in your editor/terminal
Via FetchLayer Research Chat
InstantNo IDE needed. Describe your research in plain English — "Find SaaS founders complaining about CRM pricing" — and get a downloadable CSV or JSON file with structured leads in seconds.
- Best for: instant research & lead gen
- Setup: none — just type
- Output: downloadable CSV & JSON files
Uses the same credits as the API · No additional setup
Pricing
Start free. Scale when ready.
Pay per request with no commitment, or lock in a flat monthly rate with built-in savings.
Free plan — 30 requests
Verify responses, inspect the API, no credit card required.
Pay as you go
$1.99
per 1,000 requests
$0.00199 per request · credits never expire
How credits work — no multipliers
One credit = one API call, on every endpoint and platform. No matter how many results come back, you pay for the call, not the output size. Most scraping APIs charge multipliers of 5x, 25x, even 75x per call depending on the target — here it's always 1.
- No multipliers — 1 request = 1 credit
- No monthly commitment
- Credits never expire
- Same API & MCP access as subscribers
- ∞ req/min, ∞ API keys
∞
Expiry
Credits stay until you use them. No monthly reset, no pressure to hit a quota.
0
Commitments
No subscription, no contract, no minimums. Start, pause, or scale whenever.
100%
Access
Every endpoint and MCP included. Not a limited tier — same data as any subscriber.
FAQ
Common questions.
What is FetchLayer Reddit Scraper?
FetchLayer Reddit Scraper is a REST API and MCP-compatible service for accessing publicly available Reddit data as structured JSON. It covers posts, comments, subreddit feeds, user profiles, search results, and related metadata without requiring you to maintain scrapers, parse HTML, or manage proxy infrastructure.
Is this the official Reddit API?
No. FetchLayer is an independent, third-party service not affiliated with, endorsed by, or sponsored by Reddit, Inc. We access publicly available data and structure it for developer use, in compliance with applicable law.
Is this legal?
We access only publicly available information — the same data any browser can see without logging in. We do not bypass authentication, access private content, or violate any terms of service. If you have questions about your specific use case, consult your own legal counsel.
Can I use this with AI agents?
Yes. Call the API from your agent code, or use the MCP server so your AI IDE (Cursor, Windsurf, Claude Desktop) can search Reddit directly.
What is the MCP server?
A Model Context Protocol server. You add it to your AI IDE config, and your AI can call Reddit search/scrape tools inline. One-time setup.
Does MCP cost extra?
No. MCP uses the same API credits as direct API calls. Same plan, same bill.
What about Apify?
The same scraper runs as an actor on Apify at apify.com/neatrat/reddit-scraper. If you already live in Apify — schedules, datasets, webhooks — use it there. Same data, different delivery.
What data comes back?
Titles, body text, scores, comment counts, authors, timestamps, URLs, subreddit metadata. Everything in consistent JSON.
Can I monitor keywords over time?
Yes. Search by keyword, sort by newest, and run it on a schedule. Build your own monitoring pipeline.
Can I scrape a specific subreddit?
Yes. The subreddit scraper endpoints let you pull posts, metadata, and subscriber info from any public subreddit. Pass the subreddit name and sort order — hot, new, top, or rising.
Is there a free version I can try without signing up?
Yes — the Free Reddit Scraper is a narrow browser tool for quick, one-off lookups: no account, no API key. It caps at 25 results per search (100 comments per thread) and cannot return vote scores, comment counts, nested reply trees, media, or flair — no monitoring, no automation. This API is the real product: unlimited results via pagination, every field the free tool is missing, scheduled keyword monitoring, and an MCP server your AI agent can call directly.
Open the free Reddit scraperReady to pull Reddit data into your stack?
Free tier included. No credit card. Start hitting endpoints in two minutes.
FetchLayer is an independent, third-party service. We are not affiliated with, endorsed by, or sponsored by Reddit, Inc. "Reddit" is a registered trademark of Reddit, Inc. This service accesses only publicly available data — the same information visible to any unauthenticated browser. We do not access private content, bypass authentication, or store personal data beyond what is publicly displayed. Use of this API is subject to our Terms of Service and applicable law.
Used by developers at
Individual developers or teams — not official partnerships