Hn Developer Sentiment MCP server

What developers really think about your tool.

A deterministic read on Hacker News developer sentiment for any brand, tool, or library — sentiment, mention volume, recurring themes, and feature requests across HN stories and comments, exposed as four agent-callable MCP tools. The differentiator is judgment and aggregation, not raw access: it scores, clusters, and mines public HN discussion so an AI agent can act in a single call, and returns the raw matched items alongside the aggregates so every number is auditable.

Zero setup — no API key. The Hacker News (Algolia) API is open, so this Actor boots and returns data immediately. No credentials, no approval queue, no first-run friction.

No LLM in the analysis layer — sentiment is a transparent lexicon-plus-rules scorer, so the same posts always produce the same answer.

Who is this for?

• AI agents that need a one-call read on how developers feel about a product before drafting a comparison, a launch post, or a support reply.
• DevRel and product teams tracking how a tool, framework, or release is landing with the Hacker News crowd.
• Founders and marketers validating positioning against what developers actually say in public.

Why use Hacker News Developer Sentiment?

• Zero setup — no API key, no login, no approval process. Deploy and call.
• One call, a usable answer — sentiment label, net score, volume, top themes, and representative samples in a single structured response.
• Deterministic and auditable — no model temperature, no per-call drift. Same posts plus same config always produce the same output, and the raw items ship alongside the aggregates.
• Built for agents — a Standby MCP server speaking the Streamable HTTP transport, so any MCP client can connect and call it directly.
• Cheap and fast — one HN payload per query, cached and shared across the query tools. No LLM cost in the analysis path.

How to use Hacker News Developer Sentiment

1. Deploy the Actor — run it in Standby mode on Apify. It boots with no input required and returns data immediately.
2. Connect your MCP client to the Standby endpoint (https:///mcp) using the Streamable HTTP transport.
3. Call getsentimentsummary with a query (a brand, tool, or topic) for the headline read.
4. Drill in with searchmentions, getfeaturerequests, or gettrending_discussions when you need detail. The query tools share the same cached payload per query.

The four tools

query is a brand/tool/topic string (e.g. "prisma", "tailwind"). channels, windowDays, and limit are optional and fall back to the Actor's configured defaults. channels selects HN post types — story, askhn, showhn, comment — and defaults to all (stories and comments, since HN opinion lives in the comments).

getsentimentsummary — the headline read

Aggregate sentiment, mention volume, top themes, and representative samples for a query. Input: query (required), channels?, windowDays?.

{
  "query": "prisma",
  "channelsQueried": ["story", "ask_hn", "show_hn", "comment"],
  "windowDays": 30,
  "mentionVolume": 52,
  "netSentiment": 0.18,
  "sentimentLabel": "Positive",
  "breakdown": { "positive": 29, "neutral": 16, "negative": 7 },
  "topThemes": [
    { "term": "type safety", "count": 15 },
    { "term": "migrations", "count": 12 },
    { "term": "query performance", "count": 7 }
  ],
  "topSamples": [
    {
      "title": "Prisma 6 made our migrations painless",
      "channel": "story",
      "score": 312,
      "url": "https://news.ycombinator.com/item?id=48800001",
      "createdAt": "2026-06-02T14:11:00.000Z",
      "sentiment": "Positive"
    }
  ],
  "fetchedAt": "2026-07-14T00:00:00.000Z"
}

Shortened. The full README is on GitHub.