Modelhub Port

io.github.CloudCorpRecords由 GitHub 帳號 CloudCorpRecords 發布v0.1.0更新於 Nov 3, 2026

搜尋並檢視 Hugging Face 的模型、資料集、Spaces、論文和文件。

AI 翻譯由 AI 模型根據下方的原文描述翻譯，可能有誤。

原文描述

Search and inspect Hugging Face models, datasets, spaces, papers and docs.

發布方自己的服務：Port

已驗證STDIO僅桌面知識與記憶

服務詳細資訊

識別碼: io.github.CloudCorpRecords/modelhub-port
傳輸: STDIO
執行環境: Desktop only
信任: Verified
發布於: Nov 3, 2026

安全提示

MCP 服務會接收對話中的工具呼叫請求，並可能執行外部操作。啟用前請先了解該服務能做什麼，並只授予它所需的權限。

註冊中心已驗證此條目所屬的 GitHub 帳號 CloudCorpRecords。這並不表明該帳號就是產品方。

SourceWeft 的檢查只涵蓋條目是否完整、端點是否回應；不審查伺服器的程式碼，也不審查其工具的行為。

在 README 中新增徽章

向讀者展示該 MCP 服務已收錄於 SourceWeft，徽章連結到本頁。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.CloudCorpRecords%2Fmodelhub-port.svg)](https://sourceweft.com/mcp/io.github.CloudCorpRecords%2Fmodelhub-port?utm_source=readme&utm_medium=badge)

概覽

Modelhub Port 的本機 MCP 服務；無需登入；STDIO。

暫無 AI 概覽：以下資訊來自註冊中心條目和服務本身。

安裝

在 SourceWeft 中

開啟儀表板中的 Modelhub Port，將其新增到工作區。
為需要使用其工具的對話啟用該服務。

Desktop only，透過 STDIO。 STDIO 服務會啟動本機處理程序，因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照儲存庫中的啟動說明。

README

modelhub-port

modelhub-port lets an agent explore the Hugging Face Hub without leaving its tools: look up who a token belongs to, inspect a model, dataset, or space in detail, search across all three repository kinds, list a repository's files, search the daily papers, and search or fetch pages from the Hugging Face documentation. It works from the command line or as an MCP server.

No token is needed to get started. The public Hub endpoints work anonymously, so every tool except hf_whoami runs keyless. When HF_TOKEN is set (the HUGGING_FACE_HUB_TOKEN alias is also accepted), requests carry it as a Bearer token, which raises rate limits and unlocks private or gated content the token can see. hf_whoami is the one tool that needs a token, because its whole job is to say whose token it is; without one it answers with an error naming HF_TOKEN.

Install

Or run the container image:

The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.

CLI

bash

# Whose token is configured? (requires HF_TOKEN)modelhub-port whoami
# Repository details and file listingsmodelhub-port details meta-llama/Llama-3.1-8Bmodelhub-port details squad --type datasetsmodelhub-port files meta-llama/Llama-3.1-8B
# Search models (default), datasets, or spacesmodelhub-port search "text generation" --sort downloads --limit 10modelhub-port search --type datasets --author google
# Papers and documentationmodelhub-port papers "retrieval augmented generation"modelhub-port doc-search "fine-tuning"modelhub-port doc-fetch https://huggingface.co/docs/transformers/index
modelhub-port --version

# Whose token is configured? (requires HF_TOKEN)modelhub-port whoami
# Repository details and file listingsmodelhub-port details meta-llama/Llama-3.1-8Bmodelhub-port details squad --type datasetsmodelhub-port files meta-llama/Llama-3.1-8B
# Search models (default), datasets, or spacesmodelhub-port search "text generation" --sort downloads --limit 10modelhub-port search --type datasets --author google
# Papers and documentationmodelhub-port papers "retrieval augmented generation"modelhub-port doc-search "fine-tuning"modelhub-port doc-fetch https://huggingface.co/docs/transformers/index
modelhub-port --version

Exit codes: 0 on success, 1 when a lookup fails (the error names the problem, including the HTTP status when the Hub answers with one), 2 for usage errors.

MCP server

One bin serves both faces. The mcp subcommand starts a stdio MCP server:

MCP client configuration:

json

{  "mcpServers": {    "modelhub-port": {      "command": "npx",      "args": ["-y", "@reneturcios/modelhub-port", "mcp"],      "env": {        "HF_TOKEN": "your-token-if-you-have-one"      }    }  }}

{  "mcpServers": {    "modelhub-port": {      "command": "npx",      "args": ["-y", "@reneturcios/modelhub-port", "mcp"],      "env": {        "HF_TOKEN": "your-token-if-you-have-one"      }    }  }}

The env block is optional — leave it out entirely to run keyless.

Tools

Tool	Input	What it returns
`hf_whoami`	(none)	The account the configured `HF_TOKEN` belongs to. Errors naming `HF_TOKEN` when no token is set.
`hub_repo_details`	`repo_id` (string, required), `repo_type` (string, optional), `revision` (string, optional)	Author, downloads, likes, dates, tags, and file names for one model, dataset, or space.
`hub_repo_search`	`search`, `repo_type`, `author`, `sort`, `limit`, `direction` (all optional)	A ranked list of matching repositories of the chosen kind.
`paper_search`	`query` (string, required), `limit` (number, optional)	Papers matching the query, with authors, dates, and summaries.
`hf_doc_search`	`query` (string, required), `limit` (number, optional)	Matching pages from the Hugging Face documentation.
`hf_doc_fetch`	`url` (string, required)	The text of one `huggingface.co/docs` page, with markup stripped.
`list_repo_files`	`repo_id` (string, required), `repo_type`, `revision`, `path` (optional)	The file tree of a repository at a revision, defaulting to `main`.

Hosted-only surfaces are out of scope for this rebuild: invoking Gradio spaces as tools, running jobs, managing buckets or collections, and upload/write operations are not included.

Development

bash

npm installnpm run build   # tsc -> dist/npm test        # node test runner over test/*.test.ts, no network (fake fetch fixtures)npm run dev     # run the CLI from source via tsx

npm installnpm run build   # tsc -> dist/npm test        # node test runner over test/*.test.ts, no network (fake fetch fixtures)npm run dev     # run the CLI from source via tsx