- A sentiment score is a summary of evidence you never see; the evidence is the part you can act on.
- Ten networks are readable — posts, comments, video transcripts and frames — not just the two you can publish to.
- Nooticr runs as an MCP server, so the model doing the reading is the one you already talk to.
- Twenty free credits, metered per fetch. No seat, no annual contract, no minimum.
What a sentiment score costs you
"73% positive" is a number produced by somebody else's classifier over a corpus you cannot inspect. When it moves three points you cannot tell whether the mood changed, the sampling changed, or the classifier was retrained. Every question worth asking lives underneath the number. Who said this? Under which post? Did anyone reply? The dashboard is what stands between you and the answers.
The category grew up before you had a model of your own. A vendor had to interpret for you because there was nothing else to hand the raw material to. That constraint is gone.
- Read the comment, not the label attached to it.
- Follow the thread to the reply that actually mattered.
- Ask a follow-up question that nobody wrote a dashboard filter for.
What "reads" means here
Text is the easy half. A mention inside a fourteen-minute video is invisible to a tool that only indexes captions, and that is where a great deal of honest opinion lives. Nooticr pulls the transcript and can pull frames, so "who said our name out loud" is a question with an answer.
- Posts and their comment threads, including replies.
- Video transcripts, so spoken mentions count.
- Frames, for what was on screen rather than said.
- Ten networks, including the ones with no publishing API.
Tip:If a competitor's tool can only tell you about text, it can only tell you about the part of social media that is written down.
Where the reading happens with Nooticr
Nooticr is a Model Context Protocol server. You connect it to Claude, ChatGPT, Cursor or anything else that speaks MCP, and ask in plain words. The tools fetch; your model reads. That is the whole architecture. It is also why there is no sentiment engine here to disagree with: the judgement is made by the assistant you already trust with everything else.
There is a console at nooticr.com too, for watching spend and managing scheduled sweeps, but nothing requires you to open it.
Choosing social listening software
Social listening software usually combines source collection, search and some way to review results. Before comparing vendors, check which public networks are covered, whether comments and video transcripts are searchable, and whether you can open the original source. These capabilities matter more than a long feature list if your goal is to understand what people actually said.
Nooticr works as a social listening tool that returns source material to an assistant. It is also a social listening platform with a console for reviewing usage and scheduled watches. Its model can ask follow-up questions over retrieved posts instead of being limited to a fixed set of dashboard filters.
How AI social listening should handle evidence
AI social listening is useful when a model can summarize a large set of conversations and still link each point back to the posts behind it. Treat an automated conclusion as a starting point: inspect representative sources, note gaps in network coverage and check whether the sample supports the claim. A confident summary is not a substitute for evidence.
With Nooticr, the connected assistant performs the interpretation and can answer a follow-up using the same source material. Searches are metered per network, and recurring watches quote their cost before they are created. That keeps the analysis flexible while making usage visible.
Reading the social web, network by network
Frequently Asked Questions
What is social listening?
Social media listening is the practice of finding and reading what people say about a brand, product or category in public — posts, replies, comments, and the spoken content of videos. Vendors differ on what happens next: most score it for you, and this one hands you the material. The phrase "media listening" is sometimes used more broadly to include press and forums; the social part is the half that moves fastest.
Is listening social media the same as monitoring it?
Monitoring is usually narrow — alerts on your own brand name. Listening covers the category: competitors, unprompted mentions, the objections people raise to nobody in particular. The tooling is the same; the queries are wider.
How is this different from Brandwatch or Sprinklr?
They sell you an interpretation — a dashboard, a sentiment model, an analyst seat — on an annual contract that starts around $1,000 a month and runs to six figures. Nooticr sells the fetch. You pay per call, your own model does the reading, and there is no seat to buy.
Which networks can Nooticr actually read?
Ten, including TikTok, YouTube, Instagram, X, Reddit, LinkedIn, Douyin, Xiaohongshu, Weibo and Bilibili. Reading a network and publishing to it are different things: publishing needs an OAuth app per platform, and only TikTok and YouTube have one.
Do I need to install anything?
A hosted connector at https://mcp.nooticr.com/mcp, or the same server over stdio locally. Both authenticate through the nooticr_login tool; there is no long-lived API key to paste or rotate.
What does a sweep cost?
Credits, priced per network searched, quoted before anything runs. A scheduled watch quotes first and creates nothing until you confirm with the token that quote returns — a recurring charge should not start on one click.