Not reviewed
No score, grade or rank. This listing is facts from the official MCP registry and our own checks, and it stays out of the rankings until the panel reviews it.
Sort up to 1,000 texts into your own labels with a calibrated confidence per answer. No API key.
Facts
- MCP registry
dev.classifier/classifier· 1.0.0- Endpoint
https://classifier.dev/mcp- Website
- classifier.dev
- GitHub stars
- 422
- Registry entry
- updated 19 Sep 2026
From the official MCP registry, the package registries and our own checks. JSON · Markdown
Why it's listed
- It's published in the registry under classifier.dev, a namespace the registry only gives to whoever proves they control that domain.
- It's in real use: 422 GitHub stars.
Being indexed says nothing about quality, and nobody can pay for it. Is this yours? Ask for a review.
Tools it lists 5 · about 3,514 tokens of context · checked 20 hours ago
| Tool | What it does | Hint |
|---|---|---|
classify_textsClassify texts into one label each | Sort up to 1,000 texts into exactly one of your own labels each, with confidence per answer. Use this when you have many items to triage, route, filter or bucket and do not want to read them all: search results before… | read-only |
classify_dimensionsClassify several dimensions per text | Classify each text by several named dimensions, such as team, urgency and kind, in one request. Returns a label, confidence, scores and model for each field. At most 1,000 item × dimension decisions; every field counts… | read-only |
classify_multi_labelTag texts with every label that applies | Like classify_texts, but each text gets every label that applies (possibly none), with an independent 0-1 score per label. Use this for tagging — topics of an article, components touched by a ticket — where one answer… | read-only |
count_labelsCount how many texts fall under each label | Classify up to 1,000 texts and return only a histogram: how many landed on each label, and how many the model was unsure about. Use this when you want the shape of a corpus — what share of feedback is bugs vs praise,… | read-only |
review_uncertainFind the texts the classifier was unsure about | Classify up to 1,000 texts and return only the ones whose confidence fell under a threshold (default 0.7), each with its two most likely labels. Use this after a bulk classification to decide which items deserve your… | read-only |
What https://classifier.dev/mcp answered to tools/list, asked without credentials over MCP 2025-11-25. The token figure is the size of the list as sent, divided by four; a model sees about that much before it calls anything. Full definitions, input schemas included, are in the listing's JSON under mcpTools.
How its tools read to an agent 0 errors · 5 warnings · 1 note
- warnTC11classify_dimensions1 parameter without a description: model
- warnTC11classify_multi_label1 parameter without a description: model
- warnTC15classify_dimensionsinputSchema has oneOf at the top level
- warnTC15classify_multi_labelinputSchema has oneOf at the top level
- warnTC15classify_textsinputSchema has oneOf at the top level
- noteTC24server1 of 5 tools have no outputSchema
The checks from /check and anchor check, run each day on the list above: about 3,514 tokens of definitions. Not part of the score yet. Check your own server.