Goodeye

Name: Goodeye
Author: Goodeye-Labs

by Goodeye-Labsversion 0.19.2i★ –iRuns in the cloud

Registry namedev.goodeye/goodeye

Install

Overview

Description from the maker (original English)

Design, save, and run outcome-aligned AI workflows and verifiers, with reliable image output.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs in the cloud
Transport: Streamable HTTP
Category: Design, images & audio
You need to fill in: Authorization

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on the maker’s server: what you ask it goes through their server.
You fill in yourself: Authorization

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Run this in your terminal

claude mcp add --transport http goodeye https://mcp.goodeye.dev/mcp --header 'Authorization: your-value'

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "goodeye": {
      "url": "https://mcp.goodeye.dev/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "goodeye": {
      "type": "http",
      "url": "https://mcp.goodeye.dev/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

Authorization secret required HTTP header
Bearer token: an OAuth access token from Goodeye sign-in, or a good_live_ API key (Bearer good_live_...). Anonymous requests receive 401 with WWW-Authenticate so clients can discover the OAuth flow.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain goodeye.dev (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
… Not checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
… Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Design, images & audioi

More stars than 0% of the other 2164 servers in this category
Published to the registry more recently than 13% of the other 2164 servers in this category
Basic checks equal to or better than 100% of the other 2164 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Goodeye safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: Authorization

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.19.2) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Figma Context MCP

by GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago

Install

Claude Real Video

by HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

Runs on your computer★ 2,284MITUpdated 2 months ago

Install

Figma MCP Server

by figma

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

goodeye

Goodeye is a private home for the skills your AI follows and the verifiers its work must pass.

goodeye is the command-line surface for Goodeye. The same capability reaches your agent over an MCP server and a REST API too, so it works wherever your agent runs. This CLI talks to the public /v1 REST API.

How it works

A skill is a markdown runbook your agent follows. A verifier is a check its output has to clear. Goodeye keeps both in one account you own, and three things follow from that.

Private by default. Nothing is public until you publish a template, which is a separate step you take on purpose. To share without going public, grant a named user or team access, and the verifiers the skill references go with it at the same version. Revoking works the same way.

Always in sync. goodeye skills sync mirrors your hosted skills into the directories your tools already read, so Claude Code, Codex, Cursor, and anything else reading skill files from disk run the same current version. Configuring a target is all it takes: automatic sync is on from then on, so edit a skill once and every machine picks it up on its own.

Verifiers, hosted. A verifier can be deterministic (format, schema, tests, numeric bounds) or an LLM judge for the calls no test can make, like tone or image quality. Deploy a semantic verifier once, and every skill that references it runs that exact version, on your laptop, in CI, or on the machine of someone you granted it to.

The full picture is at https://goodeye.dev/docs/overview.

Your AI agent is the primary caller

The CLI is built to be driven by an AI coding agent on your behalf, though every command also works when you run it yourself. The intended loop: you ask your agent to run a Goodeye skill, it fetches the body with goodeye skills get (or goodeye templates get @handle/slug), and it executes those instructions as your runbook instead of printing or summarizing them. The get commands wrap the body in agent-facing markers so the calling agent knows to run it. Pass --output PATH or --json when you want the raw content instead.

Install

Requires Python 3.12 or later.

uv tool install goodeye

or: pipx install goodeye

or: pip install goodeye

The goodeye command is then on your PATH. Run goodeye update to upgrade to the latest release, or goodeye update --check to see whether one is available.

Quickstart

Bring a skill you already have

A skill file on disk is a directory holding a SKILL.md plus optional siblings, which is exactly what publish expects. Importing one is a single command.

goodeye login                                     # or: goodeye register (same browser sign-in)

goodeye skills publish ~/.claude/skills/my-skill # also ~/.agents/skills, ~/.cursor/skills, or any path goodeye skills list

It lands as a private hosted skill. Nothing is public until you publish a template, which is a separate step.

Sync it to every machine and agent

Point Goodeye at the directories your tools read, then pull:

goodeye skills sync target add --preset claude    # ~/.claude/skills

goodeye skills sync target add --preset agents # ~/.agents/skills goodeye skills sync target add --preset cursor # ~/.cursor/skills goodeye skills sync

Run the same commands on your other machines and they all read the current version. Once you have a target, automatic sync is on, so they stay that way without a second command: it only pulls new and updated skills, never overwrites local edits, and reports a conflict rather than clobbering it. Turn it off with goodeye skills sync auto off and it stays off.

The skill you just published came from a directory that is now a target, so a copy of it is already there. Goodeye did not write that copy, so the first pull reports it as modified and leaves it alone. The hosted version is what you published, so adopt it once with goodeye skills sync pull --force ; from then on it is tracked like everything else.

Share it

goodeye skills grant my-skill @teammate view

goodeye skills grants my-skill

Their agent now runs your skill, and any semantic verifiers it references travel with the grant at the same version. Improve the skill and they get the improvement on their next pull.

Author a skill from scratch

goodeye design                         # prints the designer prompt; pipe it to your agent to draft a skill and its verifiers

save the draft from your agent's output (stdin keeps a stray file out of the working directory):

goodeye skills publish - \ --name my-skill \ --description "One sentence on what this does and when to use it." <<'EOF'

Body

The skill body your agent will execute. EOF

goodeye skills get my-skill # fetch it back for an agent to run

Run a public template, no account needed

Browsing, fetching, and running public templates need no sign-in.

goodeye templates list

goodeye templates get @goodeye/high-signal-chart-workflow

templates get prints the template body (the skill), and your agent follows it: it finds a dataset, renders a chart, and runs the template's pinned verifier, revising until the chart passes. That verifier run is the step your agent makes, drawing on a small per-network credit grant:

# what your agent runs against the finished chart:

goodeye verifiers run 89dcc843-d056-44d9-ae34-ebcff4903885 \ --version 1 --media-url ' ' --anonymous

Fork it into a skill of your own with goodeye templates fork @goodeye/high-signal-chart-workflow. That is the one step here that needs an account, since the fork lands in your own registry. To publish one of your own, claim a handle first with goodeye me claim-handle your-handle, then run goodeye templates publish my-skill.

What the CLI can do

These command areas cover the whole surface. Run goodeye --help or goodeye --help for the exact commands and flags, and see the full reference at https://goodeye.dev/docs/cli.

Area	What it does	Docs
`skills`	Find, save, version, run, share, and improve your private skills, including teach, optimize, audit, and local file sync	https://goodeye.dev/docs/skills
`templates`	Browse the public catalog, publish a skill as a template, and fork one to customize	https://goodeye.dev/docs/templates
`verifiers`	Deploy and run the LLM-judge checks a skill calls to grade agent output	https://goodeye.dev/docs/verifiers
`image-generators`	Deploy reusable image generators and generate images a skill can call	https://goodeye.dev/docs/image-generators
`images`	Upload and manage hosted images with stable URLs	https://goodeye.dev/docs/images
`teams`	Create teams and manage membership so a skill can be shared with a group	https://goodeye.dev/docs/teams
`referrals`	View your referral code and redeem someone else's	https://goodeye.dev/docs/referrals
`invitations`	Accept, decline, or cancel team and ownership-transfer invitations	https://goodeye.dev/docs/cli
`billing`	Upgrade to or cancel Pro (`plan upgrade` / `plan cancel`), open the billing portal, buy a one-time credit top-up, or manage automatic top-ups (`auto-topup show` / `set` / `off`)	https://goodeye.dev/docs/cli
`auth`, `me`, `usage`	Manage API keys, claim your handle, and check credit usage	https://goodeye.dev/docs/cli
`design`	Print the skill-designer prompt for your agent	https://goodeye.dev/docs/cli

Session commands sit at the top level: login, register, logout, whoami, and update.

Authentication and configuration

Sign in interactively with goodeye login or goodeye register. Both open a browser device-code flow and save your credentials on success. For agents and automation without a browser, use the email-code flow:

goodeye register --email you@example.com

goodeye register-verify --email you@example.com --code 123456

existing account: goodeye login, then goodeye login-verify

goodeye whoami shows who you are, and goodeye logout removes the local credentials. Agents and scripts can authenticate with an API key instead: create one with goodeye auth create-key --name my-agent and pass it as the GOODEYE_API_KEY environment variable.

The CLI reads credentials from GOODEYE_API_KEY first, then from ~/.config/goodeye/credentials.json (written with 0600 permissions). It targets https://api.goodeye.dev by default; override that with GOODEYE_SERVER. Full authentication details are at https://goodeye.dev/docs/cli.

CLI, MCP, or REST

The CLI is a convenience layer over the public /v1 REST API. For a stable programmatic contract, call that REST API directly (https://goodeye.dev/docs/rest-api). To drive Goodeye from an MCP client, connect to mcp.goodeye.dev/mcp (https://goodeye.dev/docs/mcp). Your skills and their verifiers reach your agent on every surface.

Documentation

Overview and mental model: https://goodeye.dev/docs/overview
Getting started: https://goodeye.dev/docs/getting-started
CLI reference, every command and flag: https://goodeye.dev/docs/cli
Skills: https://goodeye.dev/docs/skills
Verifiers: https://goodeye.dev/docs/verifiers
Templates: https://goodeye.dev/docs/templates
Public template catalog: https://goodeye.dev

Contributing

See CONTRIBUTING.md for local dev setup and the pull-request process. Issues and pull requests are welcome.

License

MIT. See LICENSE.

Goodeye

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

goodeye

How it works

Your AI agent is the primary caller

Install

or: pipx install goodeye

or: pip install goodeye

Quickstart

Bring a skill you already have

Sync it to every machine and agent

Share it

Author a skill from scratch

save the draft from your agent's output (stdin keeps a stray file out of the working directory):

Body

Run a public template, no account needed

What the CLI can do

Authentication and configuration

existing account: goodeye login, then goodeye login-verify

CLI, MCP, or REST

Documentation

Contributing

License