原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Vibeflow

作者:zorcec版本 0.26.0i★ –i在你的电脑上运行
注册名称io.github.zorcec/vibeflow

安装

概览

作者提供的说明(英文原文)

Task management for AI coding agents over MCP — board, CLI tools, plus UI annotation.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 文档、表格与办公

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "vibeflow": {
      "command": "npx",
      "args": [
        "-y",
        "@vibeflow-tools/cli",
        "--project",
        "your-value"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add vibeflow -- npx -y @vibeflow-tools/cli --project your-value

这个服务器需要在启动命令中填入值,请复制设置后自行填写。

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "vibeflow": {
      "command": "npx",
      "args": [
        "-y",
        "@vibeflow-tools/cli",
        "--project",
        "your-value"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器需要在启动命令中填入值,请复制设置后自行填写。

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "vibeflow": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@vibeflow-tools/cli",
        "--project",
        "your-value"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 zorcec 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“文档、表格与办公”中的其他服务器比较i

  • 星标数多于此分类中其他 2198 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2198 个服务器的 90% 更新
  • 基础检查结果等于或优于此分类中其他 2198 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Vibeflow 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.26.0)于前天进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Agent-Native Calendar

作者:BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

在云端运行★ 7,620MIT2个月前更新
安装

Excel MCP Server

作者:haris-musa

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

在你的电脑上运行★ 4,276MIT7天前更新
安装

MCP Server for Excel

作者:sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

在你的电脑上运行★ 847MIT4天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Vibeflow

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.

🌐 Website · 📖 Tutorial

▶ [Watch the full motion demo (MP4)](https://www.vibeflow.tools/assets/demo/showcase.mp4)


Why It Matters

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:

  • Click any element → instant task with CSS selector, URL, and source file location
  • Track on a Kanban board → see everything at a glance, drag between columns
  • Agents implement with context → no guessing, no wrong elements, no wasted iterations

Perfect for small UI fixes, broken layouts, spacing issues, and anything where pointing is faster than explaining.


Install

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.


Quick Start

# 1. Start the local server and open the Kanban board

npx @vibeflow-tools/cli kanban

2. Annotate a running app: open http://localhost:3700/inject and drag the

bookmarklet onto your bookmarks bar (or use the script tag / console snippet)

3. Click elements in your app to create tasks — the CSS selector, URL and

source location are captured for you. You can also create tasks on the board.

4. Let your agent pick up the next task with full context

npx @vibeflow-tools/cli tasks --next


See It in Action

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.


MCP Server

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.

MCP results

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 sentthe message namesthe remedy
arguments the tool's schema rejectsthe offending field (… at title)send that field, with the type the schema asks for
a tool name that does not existthe toolread tools/list; the name you sent is not one this server exposes
The schema-error class (-32602) — no vibeflow code, by design

An 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:

  • It has no entry in the code table below, and never will. Every code in that table is a vibeflow domain code that a handler produced on purpose. -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.
  • It names the offending field (… at title, … at contentB64) — the last word of the message is the field you got wrong.
  • Its code string is client-dependent, so do not key on it. Some clients normalise this class into a string of their own (the Pi MCP adapter reports it as 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:

  • A refusal is the CLI envelope. {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, …}.
  • Every refusal carries a `suggestion`, and it means "what to change". A code tells you which rule fired; the suggestion tells you the input that satisfies it. 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.
  • "Nothing to claim" is a success. 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.
  • Non-failures you must know about ride `notices`, an array of {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:
codemeaning
DRY_RUNthis was a preview; nothing was written
GIT_COMMIT_FAILEDthe task was written, the commit did not happen
GIT_COMMITTEDinformational — 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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