Omnigami Ai

io.github.omnigami-aiPublished by GitHub account omnigami-aiv0.1.1Updated Nov 7, 2026

Find omnigami skills: public catalogue search, install instructions and free-first recommendations.

Overview

AI-generated overview

Searches the public omnigami skill catalogue and returns install prompts, requirements and free-first recommendations for a described job.

What you can do
  • Search the public skill catalogue by query, kind (film, shot, images, deck) and free-only filter, with prices and pages
  • Fetch one skill's inputs, requirements, install prompt, install command and supported agents
  • Get a free-first recommendation for a described job, with reasons, a conditional alternative, or a clarification request
  • Fall back to a dated bundled snapshot with a warning when live catalogue requests fail
When to use it
Useful when you want an assistant to pick an omnigami skill for a video, image or deck job and hand you the install prompt, without browsing the site yourself. It only finds and describes skills; it does not buy, install or produce anything.
Requirements
Local stdio process run via npx from the npm package @omnigami-ai/mcp; Node 20+ and npm. Network access to omnigami.ai for live catalogue data, or the --offline flag to disable requests. No accounts, keys or environment variables.
Before you install
The README marks this a release candidate 0.1.0 not yet on npm, so the published install line may not work yet. It sends catalogue requests to omnigami.ai (no cookies, redirects rejected); jobs and product URLs are not sent, and product_url only fills the returned request. It never buys or installs, but paid picks require purchase or GitHub access handled outside the server.

Installation

In SourceWeft

  1. Open Omnigami Ai in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

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:

sh
npx -y @omnigami-ai/mcp

Claude Desktop: merge this into claude_desktop_config.json through Settings → Developer → Edit Config, then restart Desktop:

json
{  "mcpServers": {    "omnigami": {      "command": "npx",      "args": ["-y", "@omnigami-ai/mcp"]    }  }}

Claude Code: add it to the current project's .mcp.json:

sh
claude mcp add --scope project --transport stdio omnigami -- npx -y @omnigami-ai/mcpclaude mcp list

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

ToolInputsResult
search_skillsquery, optional kind (film, shot, images, deck) and boolean freeUp to eight matching skills, outputs, USD prices and pages
get_skillslugInputs, requirements, install prompt, install command and agent platforms
recommendjob, optional product_urlOne pick with reasons and a conditional alternative, a free tool, no match, or a clarification

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:

sh
npm cinpm run buildnpm testnpm run check:snapshotnpm run check:registrynode dist/src/server.mjs --offline

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+:

sh
npm run test:pack

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.

Source: README.md at commit 3fa02f0

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.1.1LatestNov 7, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts