How to Export Reddit Comments to CSV Without Reddit's API

Every method compared

Status as of August 2026.

Why the old routes closed

For years the answer to "how do I get Reddit comments without the API" was to append .json to any thread URL. It returned the entire comment tree, needed no authentication, and cost nothing. That endpoint has since been locked down and no longer returns data reliably.

The official API is technically still there, but it requires a registered OAuth application, and new app registrations are not being accepted. If you don't already hold an approved client from before the lockdown, writing code against the official API isn't an option you can act on today.

Pushshift, the archive most researchers leaned on for bulk historical pulls, is also no longer a general-purpose option. That leaves manual copy-paste, which stops being practical after a few dozen comments, or a tool that already has retrieval solved.

Exporting a thread in four steps

1. 1

   Install Reddit Comments Scraper

   Free on the Chrome Web Store. No account required to install, and no Reddit login at any point.

2. 2

   Open the side panel on the thread

   Navigate to any public Reddit thread and click the extension icon. If you're already on the thread, the URL auto-fills.

3. 3

   Set your limit and depth

   Cap how many comments to pull and how deep into nested reply chains to go. Depth 0 gets top-level only; depth 3 covers almost every real discussion.

4. 4

   Export to CSV or JSON

   One click writes a flat file with the seven columns below, ready to open in Excel, Sheets, or pandas.

What the exported CSV actually looks like

One row per comment, seven columns, with the reply structure preserved through depth and parent_id:

id,parent_id,depth,author,score,created_utc,body
t1_k8f2a1,,0,throwaway_dev,342,2026-08-02T14:21:09Z,"Been running this in prod for six months. AMA."
t1_k8f3b7,t1_k8f2a1,1,saas_builder,88,2026-08-02T14:44:51Z,"How are you handling rate limits at that volume?"
t1_k8f4c2,t1_k8f3b7,2,throwaway_dev,51,2026-08-02T15:02:18Z,"Queue plus exponential backoff. Never hit a wall."
t1_k8f5d9,,0,lurker_2019,17,2026-08-02T16:10:33Z,"Saving this thread, thanks for writing it up."

Those last two structural columns are what separate a usable export from a wall of text. A flat list of comment bodies tells you what was said; depth and parent_id tell you what each person was responding to, which is usually the part that carries the meaning.

Automating it with the API

A browser extension is the right tool while a human is choosing threads one at a time. Once you need this on a schedule, across many subreddits, or as input to a model, FetchLayer's Reddit scraping API exposes the same data over REST across 15 endpoints, with no OAuth application to register.

The /post endpoint returns the post plus its comment tree:

curl -X POST https://api.fetchlayer.dev/reddit/post \
  -H "Authorization: Bearer $FETCHLAYER_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "postId": "https://reddit.com/r/startups/comments/abc123/",
    "sort": "best",
    "limit": 100,
    "depth": 3
  }'

The same call from Node or the browser:

const res = await fetch("https://api.fetchlayer.dev/reddit/post", {
  method: "POST",
  headers: {
    "Authorization": "Bearer " + process.env.FETCHLAYER_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    postId: "https://reddit.com/r/startups/comments/abc123/",
    sort: "best",
    limit: 100,
    depth: 3,
  }),
});

const { post, comments } = await res.json();
console.log(post.title, post.numComments, comments.length);

And what comes back:

{
  "post": {
    "title": "What we learned scaling to 10k users",
    "author": "throwaway_dev",
    "score": 1284,
    "upvoteRatio": 0.94,
    "numComments": 317,
    "permalink": "/r/startups/comments/abc123/",
    "createdUtc": 1754143269
  },
  "comments": [
    {
      "id": "t1_k8f2a1",
      "author": "throwaway_dev",
      "body": "Been running this in prod for six months. AMA.",
      "score": 342,
      "replies": [ ... ]
    }
  ]
}

Using Reddit data inside an AI agent

If the destination for this data is an LLM rather than a spreadsheet, skip the export step entirely. FetchLayer ships an MCP server that exposes its endpoints as native tools, so Claude, Cursor, Windsurf, or VS Code can pull live Reddit threads into context on their own. Add one block to your MCP config:

{
  "mcpServers": {
    "fetchlayer": {
      "url": "https://mcp.fetchlayer.dev",
      "headers": {
        "Authorization": "Bearer sk-..."
      }
    }
  }
}

After that, "summarise the top objections in this thread" works against live data with no scraping code in your project at all.

What it costs

The extension is free to install and every account starts with 30 free FetchLayer requests, which is enough to export real threads before deciding anything. Beyond that, pay-as-you-go credits run $1.99 per 1,000 requests — $0.00199 a call — and never expire. Billing is per request, not per comment returned, so a 400-comment thread and a 4-comment thread cost the same single credit. There's no subscription and no monthly minimum.

Frequently asked questions