Reddit MCP server

How an agent would call it

Two steps: search returns refs, then data_fetch opens one of them. The arguments below are the arguments that were sent.

{
  "tool": "search",
  "arguments": {
    "query": "notion vs obsidian for research notes",
    "sources": [
      "reddit"
    ],
    "limit": 2,
    "runId": "<from run_begin>"
  }
}

{
  "tool": "data_fetch",
  "arguments": {
    "sourceId": "reddit",
    "ref": {
      "id": "1s26a7k"
    },
    "runId": "<from run_begin>"
  }
}

This runs against an account — send Authorization: Bearer <token> with the call. Get one at app.bedrocktap.com/dashboard/tokens; the free tier needs no card, and it reaches reddit like every other source.

What it costs. 0.45 credits per post returned, and 0.45 per fetch. The search above returned 2 posts and cost 0.9 credits; the fetch cost 0.45.

What came back

{
  "ref": {
    "id": "1s26a7k",
    "url": "https://reddit.com/r/ObsidianMD/comments/1s26a7k/notion_vs_obsidian_for_research_papers_which_one/",
    "title": "Notion vs Obsidian for research papers - which one actually works better?"
  },
  "text": "Notion vs Obsidian for research papers - which one actually works better?\n\nI’m trying to decide between Notion and Obsidian for writing a research paper. For those who’ve used either, which worked better for organizing notes, managing sources, and writing drafts? Would you recommend one over the other?…",
  "fetchedAt": "2026-09-12T14:57:54.199Z"
}

Each ref carried subreddit, subredditSubscribers, score, comments, author, createdUtc and the post’s own selftext — the same question had been asked in two communities, one of 362,542 members and one of 470,798. The fetched payload’s text was the post followed by its top comments, 4,044 characters in all, and its data split into post and comments.

Observed 2026-09-12. One call against a live source — ask again tomorrow and the rows move.

What a row contains

One row is one post: its id, the reddit.com permalink, and the title. meta carries the subreddit, the subreddit’s subscriber count, the score, the comment count, the author, the post time and the first 2,000 characters of the body. The subscriber count travels on every row on purpose — an opinion in a 30-member community is not the same finding as the same opinion in a 3-million-member one. A fetch returns the post with up to twenty top-level comments.

A question it answers. Which of these two tools do people doing this work actually keep, and what makes them switch?

Routing guidance

What an agent reads to decide whether reddit is the right source, and what to reach for when it is not.

Answers

First-hand user opinion, complaints, product comparisons and lived experience — what real people say. Fetching a post returns the flattened comment tree with depth, parent and working permalinks, and states what was left out.

Query shape

THE CAUSE OF BOTH THE ZEROS AND THE CONFIDENT-LOOKING JUNK. Bare terms are NOT ANDed — ranking is by relevance and does not require every word, so extra words BROADEN the set as precision collapses. Measured: "controller password" returned 12 hits, half containing both; "controller password reset" returned 100 hits, 1% containing all three; a five-word version returned 100 hits with NONE containing all five. Sharpen with operators: explicit `AND` between terms, "quoted phrases" for exact matches, `title:<word>` for the sharpest precision available, and `subreddit:<name>` to scope. Never leave a niche query unscoped — global search plus score thresholds selects for viral generalist noise.

Price

Priced in credits, per row, per query or per call depending on the source. Every call is quoted before it runs — `cost_estimate` returns the exact figure and spends nothing. See /pricing.

Latency

Fast — around 3.5s per search, 0.5s per fetch.

Prefer instead

`hackernews` for startup, infrastructure and developer-tooling opinion. `forums` for hands-on practitioner detail in a narrow domain.

Cannot answer

Citable primary-source facts, pricing or current events — the trust tier is community for a reason. Search volume or SEO metrics.

Caveat

ZEROS ARE AMBIGUOUS. Subreddit scope, minimum score, upvote ratio and time range all filter silently, and the score thresholds are non-zero by default. Before calling a zero evidence of absence, re-run with the thresholds at zero — every response echoes the configuration that actually applied.

Caveat

Scores and comment counts are volatile, so every payload carries the time it was retrieved. A result seen once stays replayable from the ledger.

Related sources