Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Description from the maker (original English)
Task management for AI coding agents over MCP — board, CLI tools, plus UI annotation.
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.
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": {
"vibeflow": {
"command": "npx",
"args": [
"-y",
"@vibeflow-tools/cli",
"--project",
"your-value"
]
}
}
}Run this in your terminal
claude mcp add vibeflow -- npx -y @vibeflow-tools/cli --project your-valueThis one needs values on its command line, so copy the settings and fill them in.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"vibeflow": {
"command": "npx",
"args": [
"-y",
"@vibeflow-tools/cli",
"--project",
"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 needs values on its command line, so copy the settings and fill them in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"vibeflow": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@vibeflow-tools/cli",
"--project",
"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.
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These 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 7, 2026
The registry name was verified with the GitHub account zorcec, 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 (0.26.0) reached the registry 2 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js 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.
Task management for AI coding agents — with annotation and verification built in.
Vibeflow gives your coding agent sequenced, claimable work: tasks with hierarchy, an atomic --next claim, and a review gate with verification verdicts — on a local-first kanban board that stays in your repo. Clicking a UI element to file a ticket with its exact selector, URL, and source location is built in, so visual feedback arrives as structured tasks instead of prose.
▶ [Watch the full motion demo (MP4)](https://www.vibeflow.tools/assets/demo/showcase.mp4)
AI agents write code fast, but understanding what to change is slow. Describing a UI issue in prose wastes tokens and produces wrong fixes.
Vibeflow turns visual feedback into structured tasks:
Perfect for small UI fixes, broken layouts, spacing issues, and anything where pointing is faster than explaining.
Run it once with npx — nothing to install:
npx @vibeflow-tools/cli kanban
Or install it globally for day two. This adds the short alias vf:
npm install -g @vibeflow-tools/cli
vibeflow kanban # or: vf kanban
Requirements: Node.js >= 22. Apache-2.0 licensed. No account and no cloud — every task is a JSON file in your repo.
# 1. Start the local server and open the Kanban board
npx @vibeflow-tools/cli kanban
npx @vibeflow-tools/cli tasks --next
Drag tasks across the board — Backlog → Todo → In Progress → Review → Done. Drag a card to change its status and the board persists the new column and order, even after a reload. Tag, user and type filters keep their state while you move work, and every change is written straight to the task store — so the CLI and your agent see it immediately.
Break work into a parent / child tree — Turn an epic into child tasks that keep their own status, priority and history. Expand the tree inline on the card, or create children from the terminal with vibeflow tasks --add --title "..." --parent . The same hierarchy comes back from vibeflow tasks --get , so an agent can pick up a leaf without losing the parent.
Get the whole ticket in one panel — Open any card for the full ticket: status, description, tags, priority, author, relations (children and related tasks), an activity feed and file attachments. Changes save automatically, and pasting a screenshot or file anywhere in the panel attaches it to the task instead of your Downloads folder.
Vibeflow exposes its task tools over MCP, so an agent can read and update tickets directly. Configure one server per project: a server resolves its project root once at startup and every tool call uses that root, so it cannot write into the wrong project.
stdio (recommended — no port, nothing to keep running):
{
"mcpServers": { "vibeflow": { "command": "npx", "args": ["-y", "@vibeflow-tools/cli", "mcp", "--project", "/path/to/project"] } } }
--project is required: a spawned client's working directory (often your home directory) is never trusted, and the root is validated before anything is created. Put this config _with_ the project — .mcp.json at the repo root, or your editor's workspace config using ${workspaceFolder}.
HTTP (a server you keep running):
vibeflow serve --project ./my-project # MCP endpoint at /api/mcp
Loopback-only until you configure a token. Both transports mount the identical tool set; only the transport differs.
Do not run one global server with a per-call project argument — that is deliberately not supported. One process serves one root, resolved at startup.
A type:"Research" task is refused review with RESEARCH_REPORT_REQUIRED until a .md report is attached, and over MCP the way to do that is `attach_file` with a `.md` filename — the gate looks for a .md among a task's files, so the name is what counts. There is no --report-file equivalent on this surface; the CLI flag is named in the refusal's suggestion for CLI callers only. A Research task must not carry a verification verdict (RESEARCH_VERIFY_NOT_ALLOWED) — it has no annotated UI to verify.
A tool's result carries its payload as one JSON document in `content[0].text` — that holds for every tool-level success and every tool-level refusal. There are exactly two shapes that are not JSON: a *protocol-level* failure — arguments the tool's own schema rejects, or the name of a tool that does not exist — comes back as result.isError === true with content[0].text = MCP error -32602: … and no envelope to parse. So check isError first and parse the text as JSON only when it is absent.
Those two protocol-level failures are told apart by what the message names, not by the code — the SDK reports an unknown tool through the same input-validation path, so both carry -32602 even though JSON-RPC reserves -32601 for "method not found":
| what you sent | the message names | the remedy |
|---|---|---|
| arguments the tool's schema rejects | the offending field (… at title) | send that field, with the type the schema asks for |
| a tool name that does not exist | the tool | read tools/list; the name you sent is not one this server exposes |
-32602) — no vibeflow code, by designAn input the tool's own schema rejects (create_task with no title, attach_file with no contentB64, list_tasks with limit:-1) is refused by the MCP SDK's input validation, before any vibeflow handler runs. vibeflow therefore never sees the call and cannot attach a code or a suggestion to it. What arrives is:
result.isError === true
content[0].text = "MCP error -32602: Input validation error: Invalid arguments for tool create_task: Invalid input: expected string, received undefined at title"
Three properties, all deliberate and all load-bearing:
-32602 is the JSON-RPC *invalid params* code; it is not a member of vibeflow's vocabulary, and -32602 will never appear as a row there.… at title, … at contentB64) — the last word of the message is the field you got wrong.call_failed, for instance). That label belongs to the client, not to vibeflow: the same refusal is MCP error -32602 from a plain JSON-RPC client, and greping for one client's label in another's output is how a consumer concludes the behaviour differs when it does not.Recognise the class by its shape, not by any code string: a result with isError === true whose text carries an input-validation message naming a field. The remedy is always the same — send the field it names, with the type the schema asks for. An unknown tool is NOT a member of this class: it names no field, so the rule above does not match it, and its remedy is a different one (the table above). Keying on the code alone would put the two in one bucket and send the reader after an input field when the real mistake was the tool's name.
Because tools/list is the only place a client can read the contract *before* it fails, the input shapes publish a description for every field an agent commonly gets wrong — id on each task tool (most take a full id or a unique prefix), the setVerify/verifyReason pair, limit, contentB64, the comment body, and filename (its extension decides acceptance). Read them there; there is no second chance.
Three rules for the JSON case, all of them the CLI's own conventions:
{ok:false, error:{code, message, retryable, suggestion?}} — the same shape tasks --json writes to stderr, so one parser reads both surfaces. A tool-level refusal does not set isError; it is an ordinary result whose JSON is {ok:false, …}.error.suggestion is a non-empty string on every tool-level refusal — including the generic catch wrappers (LIST_TASKS_ERROR, GET_TASK_ERROR, CREATE_TASK_ERROR, UPDATE_TASK_ERROR, ADD_COMMENT_ERROR, ATTACH_FILE_ERROR, VERIFY_TASK_ERROR, PUSH_TASKS_ERROR, CLAIM_TASK_ERROR) — and it names both surfaces where the same gate is reachable: the MCP input or tool *and* the CLI flag. A shared gate's suggestion is read by the CLI and by MCP update_task alike, so a CLI-only suggestion is an answer an MCP client cannot act on. (verify_task is the one tool that returns the CLI verify engine's own codes — E_NOT_FOUND, E_NO_BASELINE, E_NO_SELECTOR and the rest. Those codes are unchanged; where the engine attaches no text of its own, the tool substitutes a generic recovery line rather than returning a code with nothing to act on.) The one class with no suggestion is the schema error above, which never reaches a handler.claim_next_task on an empty board — or with a valid filter that matched no task — is ok with a payload of null, not an error. A claim's payload is the Task itself, so an object means a task was claimed and `null` means there was nothing to claim; that is the same answer vibeflow tasks --next --json gives with task:null and exit 0. The dryRun preview answers the same way, so a preview cannot disagree with the real call. There is no NO_TASKS_AVAILABLE code.{code, message} objects and the *same* key the CLI puts on its --json success payloads. A notice is a non-fatal signal, not a synonym for partial success — branch on code, never on the array merely being present:| code | meaning |
|---|---|
DRY_RUN | this was a preview; nothing was written |
GIT_COMMIT_FAILED | the task was written, the commit did not happen |
GIT_COMMITTED | informational — the commit succeeded; message is the sha |
A dryRun:true preview carries notices:[{code:"DRY_RUN", message:"Task would be updated"}] (or the matching phrase — Task would be created / claimed, Comment would be added, File would be attached, Verification would run); a review transition carries GIT_COMMITTED with the sha when its auto-
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