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PopNx MCPMCP servers for people who use AI · explained in plain words

ultra-e2e-test tasks

by hynix666version 0.1.1i★ –iRuns on your computer
Registry nameio.github.hynix666/ultra-e2e-test

Install

Overview

Description from the maker (original English)

List, create and move tasks through todo, in progress and done.

PopNx MCP’s three pillars

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

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 on your computer
  • Transport: stdio
  • Category: Docs, sheets & office work

Install

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

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: TASK_API_URL, TASK_API_TIMEOUT_MS

You need

Which app do you use?

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

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "ultra-e2e-test": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "TASK_API_URL",
        "-e",
        "TASK_API_TIMEOUT_MS",
        "ghcr.io/hynix666/ultra-e2e-test-mcp-server:0.1.1"
      ],
      "env": {
        "TASK_API_URL": "your-value",
        "TASK_API_TIMEOUT_MS": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add ultra-e2e-test --env TASK_API_URL=your-value --env TASK_API_TIMEOUT_MS=your-value -- docker run -i --rm -e TASK_API_URL -e TASK_API_TIMEOUT_MS ghcr.io/hynix666/ultra-e2e-test-mcp-server:0.1.1

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": {
    "ultra-e2e-test": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "TASK_API_URL",
        "-e",
        "TASK_API_TIMEOUT_MS",
        "ghcr.io/hynix666/ultra-e2e-test-mcp-server:0.1.1"
      ],
      "env": {
        "TASK_API_URL": "your-value",
        "TASK_API_TIMEOUT_MS": "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": {
    "ultra-e2e-test": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "TASK_API_URL",
        "-e",
        "TASK_API_TIMEOUT_MS",
        "ghcr.io/hynix666/ultra-e2e-test-mcp-server:0.1.1"
      ],
      "env": {
        "TASK_API_URL": "your-value",
        "TASK_API_TIMEOUT_MS": "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 one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

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

Values you fill in

  • TASK_API_URL env
    Where the task API is: an absolute http or https URL.
  • TASK_API_TIMEOUT_MS env
    How long one call to the task API may take, in milliseconds.

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

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

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 with the GitHub account hynix666, which owns the repo

  • … 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 applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Docs, sheets & office worki

  • More stars than 0% of the other 2180 servers in this category
  • Published to the registry more recently than 39% of the other 2180 servers in this category
  • Basic checks equal to or better than 100% of the other 2180 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 ultra-e2e-test tasks 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?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

Alternatives

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

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Runs in the cloud★ 7,620MITUpdated 2 months ago
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Excel MCP Server

by haris-musa

Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.

Runs on your computer★ 4,276MITUpdated 6 days ago
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Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

Runs on your computer★ 847MITUpdated 3 days ago
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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.

mcp-server

An MCP server that gives an AI assistant three tools over the task API: list_tasks, create_task and move_task. It speaks the protocol over stdio, so a client starts it as a subprocess.

It is the same architecture as the services beside it, with the transport changed (ADR-0007): src/domain holds the rules, src/application the use cases behind an outbound port, src/adapters the two things that touch the outside world — the HTTP client that calls the task API, and the MCP layer that publishes the use cases as tools — and src/main.ts wires them. npm run check:boundaries fails the build when a layer reaches past its allowlist.

The rules are repeated here rather than imported from another module (ADR-0004), and they earn their place: an illegal status move is refused here, with the legal moves named, instead of reaching the model as a 409 it usually retries.

Run it

npm install

npm start # serves over stdio; the task API must be running

Register it with a client — for Claude Code, claude mcp add tasks -- node /absolute/path/to/services/mcp-server/src/main.ts, or the equivalent entry in another client's configuration:

{

"mcpServers": { "tasks": { "command": "node", "args": ["/absolute/path/to/services/mcp-server/src/main.ts"], "env": { "TASK_API_URL": "http://localhost:8080" } } } }

VariableDefaultMeaning
TASK_API_URLhttp://localhost:8080Where the task API is. Must be an absolute http or https URL
TASK_API_TIMEOUT_MS10000How long one API call may take before it is abandoned

A value it cannot use stops the process at startup. A server that starts and then fails every tool call is worse than one that never started: the model keeps trying.

Nothing is ever written to stdout. On a stdio server stdout is the protocol channel, and one stray console.log corrupts the stream. Diagnostics go to stderr.

Tools

ToolInputAnswers with
list_tasks—Every task, its status, and the moves that status allows
create_tasktitleThe created task, in todo
move_taskid, statusThe moved task, or which moves are legal from where it is

A failure the caller can act on — a broken rule, an unreachable API — comes back as a tool result with isError: true and the reason. Only a bug here throws, because a thrown error reaches the model as a protocol error it cannot inspect.

Check

npm run verify    # import boundaries, type-check, tests

The tests drive the server through a real MCP client over an in-memory transport pair, so a tool that is registered but unreachable — a bad schema, a handler that throws — fails here rather than in someone's editor.

Publish

.github/workflows/mcp-publish.yml publishes the image to GitHub Container Registry and server.json to the MCP Registry, where clients discover servers. It uses no stored token: the image is pushed with the run's GITHUB_TOKEN, and the registry trusts GitHub's OIDC identity for the io.github. / namespace. The image is built for linux/amd64 and linux/arm64, each on a native runner, and published as one tag, so it runs natively on an Apple Silicon Mac. The two builds also stay in the registry as -amd64 and -arm64. In a private repository the arm64 runner uses paid Actions minutes once the free allowance is spent.

It runs after each release that creates a version tag, and on demand with a version. Its first job runs in the GitHub environment mcp-registry, which GitHub creates on first use; a required reviewer or a limit on which refs may publish, set there, holds the whole publish. One-time setup:

  1. Release at least once, so a v* tag exists (the release feature does this; gh release create works too).
  2. Set the repository variable MCP_PUBLISH_ENABLED=true, then run the workflow once by hand with that version. This first run is expected to fail at its last step, *Publish server.json to the MCP Registry*, with "is private or requires authentication". The images are pushed by then, but GitHub creates a new container package as private, and the registry only accepts an image anyone can pull.
  3. Make the package public: on its page, *Package settings* → *Danger Zone* → *Change visibility* → *Public*. It is OWNER/ultra-e2e-test-mcp-server, listed under the repository's *Packages*. The registry reads the image's io.modelcontextprotocol.server.name label to confirm you own it, which it cannot do for a private image. Check before going on: curl -s -o /dev/null -w '%{http_code}\n' "https://ghcr.io/token?scope=repository:OWNER/ultra-e2e-test-mcp-server:pull" prints 200 once the package is public, and 401 while it is still private.
  4. Re-run the failed job of that run (*Re-run failed jobs*). It publishes server.json, and every later release publishes on its own.

test/server-json.test.ts keeps the manifest honest in the meantime: the image label must equal the server's name, and every advertised variable must be one src/config.ts reads, with the default it really uses.

Container

docker build --tag mcp-server .

docker run --rm -i --env TASK_API_URL=http://host.docker.internal:8080 mcp-server

-i matters: the protocol is stdin and stdout.

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