Where My Hug

Which parts of an ML need Hugging Face already covers.

Connector by bikemeardsley · GitHub account verified by the MCP Registry

IndexedMITLocal (stdio)★ 1

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Install

Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/bikemeardsley-where-my-hug

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

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

Reviews

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Permissions

What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 26, 2026.

Tools: 2 read · 0 write · 0 delete · 1 not yet classified
Secrets: None asked for
Install scripts: None found
Runs as: Node.js package

Tools by what they do 3

Read from the source code; the running server may list different tools.

Read 2 · Look things up without changing anything.

where_my_hug_search
where_my_hug_verify

Not yet classified 1 · We could not tell from the name and description.

where_my_hug

Network hosts it talks to 4

agent-plugins.org · found in code
github.com · found in code
glama.ai · found in code
huggingface.co · found in code

Tools (3)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

where_my_hugWhere my hug at?
Step 1 of 3, before recommending any Hugging Face 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 for each with where_my_hug_search, and decide from what it finds which parts Hugging Face covers (use a model as is, fine-tune one, train one) and which are plain code. Follow it.
where_my_hug_searchWhere my hug at? (searched on Hugging Face)
Step 2 of 3: searches Hugging Face for each part of the need: the task's most downloaded and trending models, names holding each keyword, and the text of model and dataset cards. Returns what it found, with downloads, likes, license, age and how each turned up, to pick each part's verdict and candidates from. Then call where_my_hug_verify.
where_my_hug_verifyWhere my hug at? (checked on Hugging Face)
Step 3 of 3: checks every picked model and dataset id live on Hugging Face, 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, 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.

Signals

Stars: 1
Forks: 0
Open issues: 0
Last commit: Oct 23, 2026 (20 days ago)
Last release: Oct 27, 2026 (17 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name: io.github.bikemeardsley/where-my-hug
Version: 0.3.1
Auth: No auth
Packages: npm where-my-hug
License: MIT
Repository: github.com/bikemeardsley/where-my-hug
First seen: Oct 24, 2026
Last checked: Nov 1, 2026
Source: Official MCP Registry github-graphql

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Where My Hug MCP server. Agent Mart. https://agentmart.dev/connectors/bikemeardsley-where-my-hug (last updated 2026-11-01)