# io.github.bikemeardsley/where-my-hug (npm · where-my-hug)

Which parts of an ML need Hugging Face already covers. Every model and dataset checked live.

- Trust score: 88/100 (high trust)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- npm · `where-my-hug`: 88/100 (this document), [markdown](https://verifymcp.io/servers/bikemeardsley-where-my-hug/where-my-hug.md), [page](https://verifymcp.io/servers/bikemeardsley-where-my-hug/where-my-hug)

## Channel facts

- Registry: `npm`
- Package: `where-my-hug`
- Version: `0.3.1`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, 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 2026-11-05.

- **Supply Chain Security**: 98/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - No install/post-install scripts declared.
  - 30 of 93 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 100/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to bikemeardsley/where-my-hug).
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 8 days ago).
  - Publishes a security disclosure policy (SECURITY.md).
- **Schema Quality & AI Usability**: 60/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 665 tokens (~221/item across 3 items; 3 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 73/100
  - Stability observed for 22 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 93/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 80% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 3 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 io.github.bikemeardsley/where-my-hug MCP server?

io.github.bikemeardsley/where-my-hug runs locally as an npm package, launched with npx -y where-my-hug. 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 bikemeardsley-where-my-hug -- npx -y where-my-hug
```

### Cursor

```json
{
  "mcpServers": {
    "bikemeardsley-where-my-hug": {
      "command": "npx",
      "args": [
        "-y",
        "where-my-hug"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "bikemeardsley-where-my-hug": {
      "command": "npx",
      "args": [
        "-y",
        "where-my-hug"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add bikemeardsley-where-my-hug -- npx -y where-my-hug
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "bikemeardsley-where-my-hug": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "where-my-hug"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add bikemeardsley-where-my-hug --command npx --arg -y --arg where-my-hug
```

### Hermes

```yaml
mcp_servers:
  bikemeardsley-where-my-hug:
    command: "npx"
    args: ["-y", "where-my-hug"]
```

### Netclaw

```json
{
  "McpServers": {
    "bikemeardsley-where-my-hug": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "where-my-hug"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add bikemeardsley-where-my-hug -t stdio -c npx -a -y where-my-hug
```

### Other

```json
{
  "mcpServers": {
    "bikemeardsley-where-my-hug": {
      "command": "npx",
      "args": [
        "-y",
        "where-my-hug"
      ]
    }
  }
}
```

## 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.

### 2026-11-05 (score 88, +1)

No change was recorded against any check on this day. Stability & Change Management went from 70 to 73. That category is still filling its 30-day observation window: 21 days of observed history at the previous scan, 22 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-11-03 (score 87, +1)

No change was recorded against any check on this day. Stability & Change Management went from 63 to 67. That category is still filling its 30-day observation window: 19 days of observed history at the previous scan, 20 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-11-01 (score 86, 0)

- [functional] Package version: 0.2.0 → 0.3.1

### 2026-10-31 (score 86, +1)

No change was recorded against any check on this day. Stability & Change Management went from 53 to 57. That category is still filling its 30-day observation window: 16 days of observed history at the previous scan, 17 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-29 (score 85, +1)

No change was recorded against any check on this day. Stability & Change Management went from 47 to 50. That category is still filling its 30-day observation window: 14 days of observed history at the previous scan, 15 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-28 (score 84, +26)

- [security improvement] CVE-2023-54404 no longer affects this package
- [security improvement] Malware scan: unverified → pass
- [security improvement] Known CVEs: unverified → pass
- [functional improvement] Dependency health: unverified → 0.85

### 2026-10-27 (score 58, −20)

- [security regression] Known CVEs: fail → unverified
- [security regression] Malware scan: pass → unverified
- [functional regression] Schema quality: 192 → 221
- [functional regression] Dependency health: 0.85 → unverified
- [functional] Package version: 0.2.1 → 0.3.1

### 2026-10-25 (score 78, +1)

No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.

## MCP tools (3)

### `where_my_hug` (~270 tokens)

Where my hug at?

Step 1 of 3, before recommending any machine learning model or dataset. If compute, license, stack or data is missing, returns the questions to ask the user first: call again with the answers ("unknown" is fine). Then returns the method: split the ML need into parts, search Hugging Face and the other hubs for each with where_my_hug_search, and decide from what it finds which parts they cover (use a model as is, fine-tune one, train one) and which are plain code. Follow it.

Input parameters:

- `compute` (string): The hardware it has to run or train on, such as "one 24 GB GPU" or "CPU only". Size flags take the first "N GB" in it as the memory a model must fit in
- `data` (string): Training data there is or could be, such as "none" or "about 300 labeled photos"
- `license` (string): What the result may be used for, such as "commercial, closed source" or "research only"
- `need` (string, required): The ML need in plain words: what goes in, what should come out, and what it is for
- `stack` (string): What will call the model: language, runtime, framework

### `where_my_hug_search` (~131 tokens)

Where my hug at? (searched live)

Step 2 of 3: searches Hugging Face for each part of the need (the task's most downloaded and trending, names holding each keyword, and the text of model and dataset cards), and Kaggle, Zenodo, ModelScope and Roboflow Universe, for models and datasets alike. One found on several hubs is listed once, naming the others. Returns what it found, with downloads, likes, license, size, age and how each turned up, to pick each part's verdict and candidates from. Then call where_my_hug_verify.

Input parameters:

- `parts` (array, required)

### `where_my_hug_verify` (~264 tokens)

Where my hug at? (checked live)

Step 3 of 3: checks every picked model and dataset id live on its hub, drops the ones that are not there, flags licenses, gating, staleness and low use, sizes each model against the compute (fits, a stretch that fits only quantized, or cloud, with who hosts it), marks picks the search didn't turn up as from memory, names every hub a pick is on, shows what it found that wasn't picked, and returns the report to show the user. If nextAction is SEARCH_FIRST or RECALL_REPLACEMENTS, do what its instructions say and call again.

Input parameters:

- `components` (array, required)
- `compute` (string): The hardware it has to run or train on, such as "one 24 GB GPU" or "CPU only". Size flags take the first "N GB" in it as the memory a model must fit in
- `need` (string, required): The ML need in plain words: what goes in, what should come out, and what it is for
- `recommendation` (string): What to act on first: the one or two picks worth trying now and why (fit, license, use), then the ones to skip and why. Shown last, as "Start here"

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/bikemeardsley-where-my-hug/where-my-hug#diagnostics

## Score history

- 2026-11-05: 88
- 2026-11-04: 87
- 2026-11-03: 87
- 2026-11-02: 86
- 2026-11-01: 86
- 2026-10-31: 86
- 2026-10-30: 85
- 2026-10-29: 85
- 2026-10-28: 84
- 2026-10-27: 58
- 2026-10-26: 78
- 2026-10-25: 78
- 2026-10-24: 77
- 2026-10-23: 77
- 2026-10-22: 71
- 2026-10-21: 71
- 2026-10-20: 70
- 2026-10-19: 70
- 2026-10-18: 69
- 2026-10-17: 69
- 2026-10-16: 68
- 2026-10-15: 68
- 2026-10-14: 29
- 2026-10-13: 39

## Common questions

### What is the io.github.bikemeardsley/where-my-hug MCP server?

io.github.bikemeardsley/where-my-hug is an MCP server listed in the public MCP registry as io.github.bikemeardsley/where-my-hug. Which parts of an ML need Hugging Face already covers. Every model and dataset checked live. This page covers its npm package (where-my-hug).

### Is the io.github.bikemeardsley/where-my-hug MCP server safe to use?

io.github.bikemeardsley/where-my-hug scores 88 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. It declares no install or post-install scripts. Its build provenance is signed and verified. 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 io.github.bikemeardsley/where-my-hug MCP server expose?

io.github.bikemeardsley/where-my-hug exposes 3 tools: where_my_hug, where_my_hug_search, where_my_hug_verify. Their descriptions and schemas cost roughly 665 tokens of context every time the server is loaded.

### Is the io.github.bikemeardsley/where-my-hug MCP server still maintained?

io.github.bikemeardsley/where-my-hug is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the io.github.bikemeardsley/where-my-hug MCP server under?

io.github.bikemeardsley/where-my-hug declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

### What did VerifyMCP test on the io.github.bikemeardsley/where-my-hug MCP server?

VerifyMCP ran 16 checks on io.github.bikemeardsley/where-my-hug, covering Malware scan, Known CVEs, Install scripts, Dependency health and 12 more. Endpoint Security and Transport & Reachability do not apply to an npm package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.

## Links

- npm package: https://www.npmjs.com/package/where-my-hug
- Socket report: https://socket.dev/npm/package/where-my-hug
- Repository: https://github.com/bikemeardsley/where-my-hug
- Changelog RSS feed: https://verifymcp.io/servers/bikemeardsley-where-my-hug/where-my-hug.xml
- Changelog JSON feed: https://verifymcp.io/servers/bikemeardsley-where-my-hug/where-my-hug/changelog.json
- Trust report (JSON): https://verifymcp.io/servers/bikemeardsley-where-my-hug/where-my-hug.json
- HTML version of this page: https://verifymcp.io/servers/bikemeardsley-where-my-hug/where-my-hug