--- title: "Reddit and HN Listening on Mac: Find the Threads" description: "Search Reddit and Hacker News for the threads asking for what you built, from your own Mac. No alerting service and no social listening subscription." date: 2026-08-28 author: "Ben Racicot" tags: ["Outreach", "Reddit", "Hacker News", "MCP", "Privacy", "macOS"] type: "article" canonical: "https://modelpiper.com/blog/reddit-hn-keyword-alerts-mac" --- # Reddit and HN Listening on Mac: Find the Threads > Search Reddit and Hacker News for the threads asking for what you built, from your own Mac. No alerting service and no social listening subscription. ## TL;DR ToolPiper exposes Reddit and Hacker News search as MCP tools, so an agent can find the threads where people describe the problem you solve. The useful output is not a mention count, it is a short list of conversations worth reading. The threads that matter are not the ones that name your product. They are the ones where somebody describes the problem your product solves and asks whether anything does that. Brand alerting misses those completely, because your brand is the one word the thread does not contain. What you want is problem search, run regularly, over the two places developers ask. ## Search the problem, not the brand Write down the sentence a person would type when they have your problem and do not know you exist. That sentence, not your product name, is the query. It usually contains the constraint rather than the category: "without a subscription", "runs offline", "on an M1". Then read the results as conversations rather than as a count. A listening tool that reports a mentions number invites you to watch the number. Ten threads you have actually read is worth more than a chart, and at this scale reading them is a few minutes. Start with what this does not do. There is no search volume here, no keyword difficulty, no cost per click, no backlink index, no domain overview, no stored rank history and no site crawler. If you need any of those, a vendor backed suite such as OpenSEO has them and ToolPiper does not. OpenSEO is open source under MIT with nine agent skills, and its data is metered through DataForSEO on every keyword, SERP and backlink call. Verified 2026-08-28. ## How ToolPiper does it `reddit_search` and `hn_search` are exposed over the local MCP server, so any MCP client can call them. An agent can run several problem queries, drop the threads that are years old or already answered, and hand you the short list. Both are part of the Outreach family, alongside Search Console and the content queue, so the thread you found and the note you write about it live in the same place. ## What you need macOS 26 or later on Apple Silicon, ToolPiper, and an MCP client if you want an agent to run the queries on a schedule rather than you running them by hand. ## A word on how to show up Finding the thread is the easy half. Both communities are hostile to vendors who arrive with a pitch, correctly so. Answer the question that was asked, say plainly what you work on, and accept that most threads are not yours to reply to. ## Limits worth knowing before you start ToolPiper needs macOS 26 or later on Apple Silicon, and the SERP capture drives Google Chrome over the DevTools Protocol, so Chrome has to be installed. One capture is a sample, not a measurement: AI Overview presence rotates by session, location and personalisation, so a single run tells you what happened once, in your browser, from where you are sitting. Search Console tools sit behind Google OAuth on your own account. ## Try it Download ToolPiper and run three problem queries for the thing you build. Read every result. The rung badge above names the plan the Outreach family sits on, resolved from the pricing catalog. _Part of the SEO tools guide for Mac. The roundup covers SERP capture, keyword discovery, rank checks, Search Console and listening in one place._ ## Steps ### 1. Install ToolPiper and connect your MCP client Download from [modelpiper.com/download](/download), launch, and register the server: `claude mcp add toolpiper -- ~/.toolpiper/mcp`. The listening tools appear alongside the rest. ### 2. Write three problem queries, not brand queries For each, describe the situation a person is in when they need what you built, in their words. Include the constraint that makes your answer the right one. Three good queries beat twenty broad ones, because you are going to read every result. ### 3. Run them across both communities Ask the agent to search Reddit and Hacker News for each query and return the threads with their age and comment count. Different audiences, different phrasing: the same problem is often described one way on one site and another way on the other. ### 4. Filter to what is still live, then read it Drop anything old enough that a reply would be archaeology, and anything already answered well. What survives is usually a handful of threads. Read them in full before deciding whether you have anything useful to add. ### 5. Queue the ones worth answering Put the survivors in the content queue with a note on what you would actually say. The gap between finding a thread and answering it is where most of this work dies, and a queue is what closes it. ## FAQ ### Is this a social listening or alerting service? No. It is search you run, not a monitored feed with alerts. There is no stored history and no mentions dashboard. If you want scheduled alerting with a trend line, that is a different category of product. ### Does it post for me? Posting is a separate tool and a separate decision. Finding a thread and replying to it should not be one keystroke, in both communities. ### Do I need a Reddit account? Search works without connecting an account. Posting requires connecting one over OAuth. ### Why search the problem instead of my brand? Because the threads worth finding are written by people who do not know you exist, so your brand is the one word that is missing. Brand search finds people already talking about you, which is a smaller and later set.