maxsentiment

An MCP server that tells you what people actually think about any social post.

Paste a link. It reads every comment, finds the themes, and shows you which themes got the most engagement. Works on LinkedIn, Instagram, X, YouTube and Reddit.

What it does · Examples · Platforms · Quick start · FAQ

What it does

Reading a post's comments by hand is impossible once there are more than a few dozen. This does it for you. Two things:

1. It reads the engagement on a post. Every comment and every reply. On any platform you support: LinkedIn, Instagram, X, YouTube, Reddit. You paste a link, it pulls the lot.

2. It makes sense of it. It uses the OpenAI Decisions API to classify every comment, and GPT-5 to work out the themes. Then it buckets the result by engagement:

this theme got this much engagement. that theme got that much. ranked, top to bottom.

So instead of "412 comments," you get the real breakdown:

38% of the engagement was people asking for proof. 22% was price complaints. 15% was praise. 9% was "not for us."

That is the whole point. What the conversation was actually about, and which parts of it people actually cared about. (A comment counts for more than a like, because writing takes more effort than tapping. So the ranking reflects real attention, not drive-by taps.)

Related MCP server: Caelario MCP

Examples

Point it at a post and you get four things:

A real run. Kunal Shah's "WhatsApp" post on X, 360 replies:

The top of the raw feed was all promo spam (trading pitches, ads). maxsentiment drops that on its own, and the real chorus underneath is one clear theme: "WhatsApp has become a spam and ads machine." Under it: give us a separate business inbox, make the AI opt-in, fix the fraud and impersonation. Loudest single reply: "it no longer feels like a messenger." Not hostile. A clear, united ask, which is far more useful to know than a star rating.

Want the showcase filled in with specific posts (say the same Deepinder Goyal topic across LinkedIn and X, or a Kunal Kamra post across Instagram and X, to show one theme repeating on every channel)? Those are live runs. See Quick start.

Platforms

Every platform reads the same internal web API your browser uses. Nothing is logged in, made, or evaded. You export your session cookies once, with a browser extension. YouTube needs nothing.

Quick start

pip install -r requirements.txt

Register the MCP server with your agent (Claude Code or Desktop). Command python, args ["server.py"], env { "OPENAI_API_KEY": "sk-..." }. Then just talk to it:

What are people saying on https://x.com/user/status/123456?
Which themes got the most engagement, and how did people feel?

The agent walks you through exporting cookies (it points you at the open-source "Get cookies.txt LOCALLY" extension), reads the post, and reports back. The skill in skills/maxsentiment/ teaches it the whole workflow.

The two calls it runs under the hood:

ms_post(url)         pull every comment on the post
ms_build_tree(...)   group them by theme, ranked by engagement

How it's built

• Platform clients read each site's own internal web API with your session cookies.

• The OpenAI Decisions API classifies every comment. Fast, deterministic, cheap: a few thousand comments costs under a dollar. GPT-5 names and groups the themes.

• A spam filter runs first, so promo, ads and giveaways never pollute the ranking.

FAQ

No. It never logs in, posts, likes, follows, or makes accounts. It reads public comments using a session cookie you exported yourself. It only reads.

In ~/.maxsentiment/, outside any repo, one file per platform. They're never committed and never sent anywhere except the platform they belong to. Scraped comments write to maxsentiment_runs/, which is .gitignored.

Scraping is free. The theme analysis uses the OpenAI Decisions API, where input is cheap and output is free, so a run over a few thousand comments is well under a dollar. The key is read from OPENAI_API_KEY.

Any agent that supports a local MCP server (Claude Code, Claude Desktop, and others). Or use the Python library directly.

LinkedIn serves its comments as a heavier server-driven page, not a clean data feed, so it needs a fully fresh session. Same input and output as the others, just more machinery behind it.

Privacy

Sessions live in ~/.maxsentiment/, outside any repo, so cookies never get committed. Scraped comments write to maxsentiment_runs/, which is .gitignored. This repo is the tool. Whatever you point it at stays on your machine.

Not for

Making fake accounts, scraping strangers at scale, evading blocks, or building a dossier on a private person. It drives your own session against public posts. Keep it there.

License

MIT.