Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Description from the maker (original English)
List, create and move tasks through todo, in progress and done.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
TASK_API_URL, TASK_API_TIMEOUT_MSYou 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:0.1.1Fill in the empty values before running it.
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.
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.
TASK_API_URL envTASK_API_TIMEOUT_MS envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account hynix666, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
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
Agent-Native Google Calendar - manage events, sync, and public booking
Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
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.
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.
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" } } } }
| Variable | Default | Meaning |
|---|---|---|
TASK_API_URL | http://localhost:8080 | Where the task API is. Must be an absolute http or https URL |
TASK_API_TIMEOUT_MS | 10000 | How 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.
| Tool | Input | Answers with |
|---|---|---|
list_tasks | — | Every task, its status, and the moves that status allows |
create_task | title | The created task, in todo |
move_task | id, status | The 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.
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.
.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:
v* tag exists (the release feature does this; gh release create works too).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.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.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.
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.