# classifier.dev

> Sort up to 1,000 texts into your own labels with a calibrated confidence per answer. No API key.

- name: dev.classifier/classifier
- version: 1.0.0
- connection class: R0 (autonomous)
- trust: 93/100
- quality: 86/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/dev.classifier%2Fclassifier
- tools: https://api.protogrid.dev/v1/servers/dev.classifier%2Fclassifier/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

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


## Trust

- hygiene: 100
- liveness: 100
- freshness: 85
- provenance: 85
- drivers: +repository +dns-namespace +website +reachable +uptime-99% ~updated-30d-ago
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 86/100 (good)

### protocol: 75 (weight 25)

- warn `protocol.modern`: newest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
- n/a `protocol.stateless`: only applies to 2026-07-28 servers
- pass `protocol.transport`: streamable HTTP
- n/a `protocol.list_ttl`: only applies to 2026-07-28 servers

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 100 (weight 30)

- pass `tools.descriptions`: every tool has a description
- pass `tools.description_length`: descriptions are concise
- pass `tools.schemas`: every tool has an object input schema
- pass `tools.annotations`: 5 of 5 tools declare readOnlyHint or destructiveHint
- pass `tools.directory_hints`: every tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHint
- pass `tools.token_cost`: about 3,465 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 75 (weight 15)

- warn `stability.changes`: 8 tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 5, about 3,465 tokens to load them all
- tool set hash: 2f2d6b3d655c7a9b9d996013b219a8ac
- tools last changed: 2026-10-04T13:49:48.725Z
- badge: [![protogrid quality](https://protogrid.dev/badge/dev.classifier/classifier.svg)](https://protogrid.dev/servers/dev.classifier/classifier)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

- 2026-10-04 `review_uncertain` changed (inputSchema, annotations)
- 2026-10-04 `count_labels` changed (inputSchema, annotations)
- 2026-10-04 `classify_multi_label` changed (inputSchema, annotations)
- 2026-10-04 `classify_dimensions` changed (inputSchema, annotations)
- 2026-10-04 `classify_texts` changed (inputSchema, annotations)
- 2026-09-24 `classify_multi_label` changed (inputSchema, annotations)
- 2026-09-24 `classify_dimensions` changed (inputSchema, annotations)
- 2026-09-24 `classify_texts` changed (inputSchema, annotations)

Full history: https://api.protogrid.dev/v1/servers/dev.classifier%2Fclassifier/changes

## Remotes

- https://classifier.dev/mcp (streamable-http, auth none, reachable true, uptime30d 0.99122804)

## Packages

_none_

## Tools (5)

- `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 ambiguous categories.
- `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 text. Labels scoring >= 0.7 are kept.
- `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 not use it for fewer than about five items you can already see — just decide. For default Jev, confidence is calibrated (answers >= 0.9 are right ~82-92% of the time; < 0.5 about 30-60%); these measurements do not apply to experimental Laya. so act on the sure ones and look at the rest yourself, or pass tier "smart" to have the unsure ones re-asked of a reasoning model.
- `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 thousand individual answers into context. Use classify_texts when you need the answer per item.
- `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 the ones to read. Returns the index of each item so you can map back to your list.