
Omnigami Ai
io.github.omnigami-ai由 GitHub 帳號 omnigami-ai 發布v0.1.1更新於 Nov 7, 2026
Find omnigami skills: public catalogue search, install instructions and free-first recommendations.
概覽
搜尋 omnigami 公開技能目錄,回傳安裝提示、所需條件,並針對描述的工作給出免費優先的推薦。
- 可以做什麼
- 依關鍵字、類型(film、shot、images、deck)與僅免費條件搜尋公開技能目錄,含價格與頁面
- 取得單一技能的輸入、需求、安裝提示、安裝指令與支援的代理平台
- 針對描述的工作給出免費優先的推薦,附理由、備選方案或澄清提問
- 即時目錄請求失敗時,退回附日期的內建快照並顯示警告
- 適用情境
- 適合讓助理為影片、圖片或簡報工作挑選 omnigami 技能並直接提供安裝提示,不必自行瀏覽網站。它只負責尋找與說明技能,不購買、不安裝、不產生成品。
- 執行需求
- 透過 npx 從 npm 套件 @omnigami-ai/mcp 啟動的本機 stdio 程序,需要 Node 20+ 與 npm。需連線 omnigami.ai 取得即時目錄資料,或使用 --offline 參數關閉請求。不需帳號、金鑰或環境變數。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Omnigami Ai,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
omnigami MCP
Find an omnigami skill from your agent: search the public catalogue, get its install prompt, or describe the job for a free-first recommendation. Runs locally over stdio. It never buys, installs or generates a deliverable.
Release candidate 0.1.0, not yet on npm. The install lines below work once
@omnigami-ai/mcp is published. MIT licensed (LICENSE).
Install — once published
Requires Node 20+ and npm. The package starts with:
Claude Desktop: merge this into claude_desktop_config.json through
Settings → Developer → Edit Config, then restart Desktop:
Claude Code: add it to the current project's .mcp.json:
Cursor: merge the same mcpServers JSON into .cursor/mcp.json in the
project, then enable the server in Cursor's MCP settings. For a global setup use
~/.cursor/mcp.json.
If a GUI cannot find npx, use its absolute path. On Windows use "command": "cmd" and "args": ["/c", "npx", "-y", "@omnigami-ai/mcp"].
Add --offline after the package name to disable catalogue requests.
The prototype was exercised in Claude Code and Inspector CLI. Desktop and Cursor configuration follows their official documentation; their GUIs have not been exercised. A skill's own agent support is separate: catalogue results distinguish Claude Code's tested status from other listed agents. Desktop guide, Claude Code configuration, Cursor configuration.
Tools
For example, ask your agent: “Find a free launch-video skill for my working web app, wide for our website.” Describe the destination, shapes, input access, budget, theme and owned skills. A general launch defaults to free Product film. Paid picks explain the price and purchase/GitHub access requirements. No bundles are promoted. Two deliverables ask which comes first and name both choices.
Version one uses deterministic English routing. The host should inspect the user's authorized product material and pass a self-contained brief. The server does not inspect product URLs, verify screens or infer business facts. Complex implications and negations still need host judgment. A supplied recording has no verified match while the published catalogue lists no recording input.
Public data and privacy
The server reads fixed public paths on https://omnigami.ai: /llms.txt, each
/skills/<slug>/install.md, and the corresponding skill page. It uses the live
list for prices and availability and refreshes details on demand. The cache
lasts 15 minutes in memory. Requests have a four-second timeout and 1.5 MB limit,
reject redirects and send no cookies. Failures fall back to the dated bundled
snapshot with an explicit warning; detail failures are labelled separately.
Free-page prompts come from the site's Copy install prompt. Paid pages omit
that button, so their public install.md Ask line is wrapped in the site's same
prompt format; prompt_source identifies this fallback.
The bundle contains 36 public skills, checked on 2026-11-07. No keys, accounts,
analytics or runtime disk cache. Jobs and product URLs are never sent to the
site. product_url only fills the returned request. The runtime reads its own
installed modules/data, never the user's product repo or credentials. Your host
client controls its own model usage and conversation storage.
Develop locally — available now
From this source folder:
The server waits for MCP messages on stdin. For an unpublished client setup,
replace the npx entry with absolute Node and dist/src/server.mjs paths.
check:snapshot compares every bundled skill's price, availability, install
command, prompt, inputs and outputs against live public pages. Inside the site
workspace it also compiles the real site/src/data/skills.ts, finder helpers
and availability helper. Use -- --site /path/to/site explicitly or -- --live
for the independent public repository. Network/parse failure fails the check.
npm run snapshot refreshes public data; review the diff and rebuild afterward.
CI tests Node 20, 22 and 24 and checks live snapshot freshness. For the clean tarball install plus Inspector CLI smoke test, use Node 24.22.1+:
The script uses a temporary clean export, packs and installs its tarball,
lists the three tools and calls each once, then removes its temporary files.
Inspector 2.14.0 is fetched as a development tool and is absent from the package.
The runtime pins @modelcontextprotocol/sdk 1.32.2; the build copies modules and
public data into dist without fetching anything.
Release and contact
Releases are published from version tags by the release.yml workflow, with npm
provenance and no stored token. The MCP Registry entry is publishing/server.json.
Report bugs at GitHub Issues. For questions or a private report, email [email protected]. Include your Node/client versions, the tool and a minimal example; omit private product data.
omnigami is a product of Auberon LLC and is not affiliated with Anthropic.
來源:README.md,提交 3fa02f0
工具
0版本歷史
1- v0.1.1最新Nov 7, 2026
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