# classifier.dev (remote · classifier.dev)

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

- Trust score: 68/100 (medium)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-28

## Components

- remote · `classifier.dev`: 68/100 (this document), [markdown](https://verifymcp.io/servers/dev-classifier-classifier/classifier.md), [page](https://verifymcp.io/servers/dev-classifier-classifier/classifier)

## Channel facts

- Endpoint: `https://classifier.dev/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-28.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS enforcement could not be verified: the plaintext port answered with HTTP 405, which proves neither a plaintext path nor enforcement.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 60/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1863 tokens (~372/item across 5 items; 5 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 30/100
  - Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 98/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 94% of tool parameters carry a description.
  - Structured output schemas are declared (80% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the classifier.dev MCP server?

classifier.dev is a hosted endpoint at https://classifier.dev/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http dev-classifier-classifier 'https://classifier.dev/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "dev-classifier-classifier": {
      "url": "https://classifier.dev/mcp"
    }
  }
}
```

### VS Code

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

### Codex

```toml
[mcp_servers.dev-classifier-classifier]
url = "https://classifier.dev/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "dev-classifier-classifier": {
      "type": "remote",
      "url": "https://classifier.dev/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add dev-classifier-classifier --url 'https://classifier.dev/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  dev-classifier-classifier:
    url: "https://classifier.dev/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "dev-classifier-classifier": {
      "Transport": "http",
      "Url": "https://classifier.dev/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add dev-classifier-classifier -t streamable-http -u 'https://classifier.dev/mcp'
```

### Other

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

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-28 (score 68, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-27 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-25 (score 67, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-24 (score 67, +1)

- [cosmetic] “classify_texts” reworded the description of “model”

### 2026-09-23 (score 66, 0)

- [cosmetic] “classify_texts” reworded the description of “model”

### 2026-09-22 (score 66, +1)

- [cosmetic] “classify_texts” reworded the description of “model”

### 2026-09-21 (score 65, −1)

- [security] Tool “classify_texts” rewrote its description, which is the text the model reads
- [functional regression] Schema quality: 257 → 296
- [functional regression] Tool coverage: 100% → 92%
- [cosmetic] “classify_dimensions” added an optional parameter “model”
- [cosmetic] “classify_dimensions” added an optional parameter “processing”
- [cosmetic] “classify_multi_label” added an optional parameter “model”
- [cosmetic] “classify_multi_label” added an optional parameter “processing”
- [cosmetic] “classify_texts” added an optional parameter “model”
- [cosmetic] “classify_texts” added an optional parameter “processing”
- [cosmetic] “classify_dimensions” reworded the description of “tier”
- [cosmetic] “classify_texts” reworded the description of “tier”

### 2026-09-20 (score 66, +1)

- [security] The server rewrote its instructions, which are the text every model session reads
- [functional regression] Tool coverage: 100% → 80%
- [functional regression] Schema quality: 1072 → 1287
- [functional improvement] Stability: unverified → 0.03
- [functional] New tool “classify_dimensions”

## MCP tools (5)

### `classify_texts` (~617 tokens)

Classify 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 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.

Input parameters:

- `include` (array): With url: return article.markdown and/or article.html at no extra scrape cost. Omit for compact output.
- `inputs` (array): 1 to 1,000 texts to classify. Results come back in the same order.
- `instructions` (string): Optional extra criteria, e.g. "judge only the service, ignore the food".
- `labels` (array, required): 2 to 100 category names. Descriptive names classify better: "urgent bug" beats "p0". Add a label like "none of these" when none-of-the-above is a real outcome.
- `model` (string): Jev is default. Default/explicit jev inputs over 32,000 characters use paid Fast-only long context: up to 250,000 original cl100k_base context tokens total, 20 documents, 32 decisions and a 1 MB body…
- `processing` (string): Optional. Implies Laya if model is omitted; has no effect with explicit Jev. With Laya, omit to select fast for one decision or bulk for batches automatically. Explicit fast accepts one decision. Sha…
- `tier` (string): fast (default) or smart, which re-asks answers under 0.7 confidence of a reasoning model (slower, single-label only). Independent of the Laya processing lane.
- `url` (string): Scrape one public URL instead of inputs/items. Requires funded workspace access. Context.dev costs $0.0022 per billed attempt plus classification; long articles need Fast. Errors disclose retained ch…

Output parameters:

- `model` (string)
- `results` (array): One per input, in input order.
- `tier` (string)
- `usage` (object)

### `classify_dimensions` (~329 tokens)

Classify 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 toward the quota. Use per-dimension instructions to define ambiguous categories.

Input parameters:

- `dimensions` (object, required): Named dimensions. Each is a label array or {labels, instructions}. At most 1,000 item × dimension decisions; definitions at most 16,000 characters combined.
- `include` (array): With url: return article.markdown and/or article.html at no extra scrape cost. Omit for compact output.
- `instructions` (string): Optional extra criteria, e.g. "judge only the service, ignore the food".
- `items` (array): 1 to 1,000 texts to classify. Results come back in the same order.
- `model` (string)
- `processing` (string): Optional. Implies Laya if model is omitted; has no effect with explicit Jev. Omit for automatic fast/bulk selection based on item × dimension decisions.
- `tier` (string): fast (default) or smart, which re-asks answers under 0.7 confidence of a reasoning model (slower, single-label only). Independent of the Laya processing lane.
- `url` (string): Scrape one public URL instead of inputs/items. Requires funded workspace access. Context.dev costs $0.0022 per billed attempt plus classification; long articles need Fast. Errors disclose retained ch…

### `classify_multi_label` (~330 tokens)

Tag 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 is not enough. Set max_labels to cap how many come back per text. Labels scoring >= 0.7 are kept.

Input parameters:

- `include` (array): With url: return article.markdown and/or article.html at no extra scrape cost. Omit for compact output.
- `inputs` (array): 1 to 1,000 texts to classify. Results come back in the same order.
- `instructions` (string): Optional extra criteria, e.g. "judge only the service, ignore the food".
- `labels` (array, required): 2 to 100 category names. Descriptive names classify better: "urgent bug" beats "p0". Add a label like "none of these" when none-of-the-above is a real outcome.
- `max_labels` (integer): At most this many labels per text, most likely first.
- `model` (string)
- `processing` (string): Optional. Implies Laya if model is omitted; has no effect with explicit Jev. Omit to select fast for up to four labels on one text, or bulk for larger work automatically.
- `url` (string): Scrape one public URL instead of inputs/items. Requires funded workspace access. Context.dev costs $0.0022 per billed attempt plus classification; long articles need Fast. Errors disclose retained ch…

Output parameters:

- `results` (array)
- `usage` (object)

### `count_labels` (~201 tokens)

Count 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, how many search results are relevant — without pulling a thousand individual answers into context. Use classify_texts when you need the answer per item.

Input parameters:

- `inputs` (array, required): 1 to 1,000 texts to classify. Results come back in the same order.
- `instructions` (string): Optional extra criteria, e.g. "judge only the service, ignore the food".
- `labels` (array, required): 2 to 100 category names. Descriptive names classify better: "urgent bug" beats "p0". Add a label like "none of these" when none-of-the-above is a real outcome.
- `unsure_below` (number): Answers with confidence under this count as unsure.

Output parameters:

- `counts` (object): Label -> how many texts, every label present.
- `total` (integer)
- `unsure` (integer): How many answers fell under unsure_below.
- `unsure_below` (number)

### `review_uncertain` (~198 tokens)

Find 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 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.

Input parameters:

- `below` (number): Return items with confidence under this.
- `inputs` (array, required): 1 to 1,000 texts to classify. Results come back in the same order.
- `instructions` (string): Optional extra criteria, e.g. "judge only the service, ignore the food".
- `labels` (array, required): 2 to 100 category names. Descriptive names classify better: "urgent bug" beats "p0". Add a label like "none of these" when none-of-the-above is a real outcome.

Output parameters:

- `below` (number)
- `total` (integer)
- `uncertain` (array)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/dev-classifier-classifier/classifier#diagnostics

## Score history

- 2026-09-28: 68
- 2026-09-27: 68
- 2026-09-26: 67
- 2026-09-25: 67
- 2026-09-24: 67
- 2026-09-23: 66
- 2026-09-22: 66
- 2026-09-21: 65
- 2026-09-20: 66
- 2026-09-19: 65

## Common questions

### What is the classifier.dev MCP server?

classifier.dev is an MCP server listed in the public MCP registry as dev.classifier/classifier. Sort up to 1,000 texts into your own labels with a calibrated confidence per answer. No API key. This page covers its hosted endpoint (https://classifier.dev/mcp).

### Is the classifier.dev MCP server safe to use?

classifier.dev scores 68 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the classifier.dev MCP server expose?

classifier.dev exposes 5 tools: classify_texts, classify_dimensions, classify_multi_label, count_labels, review_uncertain. Their descriptions and schemas cost roughly 1,675 tokens of context every time the server is loaded.

### Does the classifier.dev MCP server require authentication?

No. We connected to classifier.dev without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the classifier.dev MCP server still maintained?

classifier.dev is still listed as active in the MCP registry. We last reached this channel on 28 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://classifier.dev/mcp
- Repository: https://github.com/mrmps/classifier-dev
- Website: https://classifier.dev/
- Changelog RSS feed: https://verifymcp.io/servers/dev-classifier-classifier/classifier.xml
- Changelog JSON feed: https://verifymcp.io/servers/dev-classifier-classifier/classifier.json
- HTML version of this page: https://verifymcp.io/servers/dev-classifier-classifier/classifier