classifier.dev

Last 30 days

Uptime

100%

Response time

270 ms typical, 270 ms slowest 5%

Last check

4 h ago

Next check

in 2 h

How to call it

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "classifier-dev": {
      "type": "http",
      "url": "https://classifier.dev/mcp"
    }
  }
}

5 tools

• classify_texts

  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 opening them, tickets, log lines, changed files, feedback. Do

• classify_dimensions

  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 toward the quota. Use per-dimension instructions to define am

• classify_multi_label

  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 is not enough. Set max_labels to cap how many come back per te

• count_labels

  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, how many search results are relevant — without pulling a thousa

• review_uncertain

  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 own attention: the confident answers can be trusted, these are

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