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

Quarterback

作者:bobbyrgoldsmith版本 1.0.1i★ –i在你的电脑上运行
注册名称io.github.bobbyrgoldsmith/quarterback

安装

概览

作者提供的说明(英文原文)

Strategic task prioritization and agent orchestration for multi-project operators

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

  • PyPI已安装 Python 的 uv(用于 uvx 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": {
    "quarterback": {
      "command": "uvx",
      "args": [
        "quarterback"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add quarterback -- uvx quarterback

在 Cursor 中打开

或者自己复制设置

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

{
  "mcpServers": {
    "quarterback": {
      "command": "uvx",
      "args": [
        "quarterback"
      ]
    }
  }
}

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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "quarterback": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "quarterback"
      ]
    }
  }
}

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 bobbyrgoldsmith 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 2197 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2197 个服务器的 5% 更新
  • 基础检查结果等于或优于此分类中其他 2197 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

Quarterback 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(1.0.1)于8个月前进入注册中心。

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 Python (uv)。

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★ 4,276MIT6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。

Quarterback

Read the field. Call the play.

Strategic task prioritization and agent orchestration for multi-project operators.


Every other AI task manager breaks down one project into subtasks. Quarterback helps you decide which of your ten projects to prioritize right now — using a 5-factor weighted scoring engine, organizational context, and time-aware planning. It runs locally, costs nothing, and works as both a standalone CLI and an MCP server for Claude.

What Makes Quarterback Different

FeatureQuarterbackTaskMaster AIShrimp Task Manager
Multi-project prioritization5-factor weighted engineSingle-project breakdownSingle-project
Advisory document systemAnalyze articles against your goalsNoNo
Agent orchestrationAutonomy levels + webhooksNoNo
Time-aware planningWorking hours, lunch, buffer timeNoNo
Organizational contextGoals, constraints, workflowsNoNo
Knowledge wiki (Playbook)LLM-maintained wiki for cross-session consistencyNoNo
Conflict detectionCross-project scheduling conflictsNoNo
Standalone CLIFull CLI without AI runtimeRequires AIRequires AI
CostFree (MIT)FreeFree

Quick Start

# Install

pip install quarterback

Initialize (creates ~/.quarterback/)

quarterback init

Interactive setup wizard — walks you through org, goals, workflows, projects, constraints

quarterback setup

Add your first project and tasks

quarterback add "Launch landing page" --project "My Startup" --priority 4 --effort 3 --impact 5 quarterback add "Write blog post" --project "Content" --priority 3 --effort 2 --impact 3

See what to work on

quarterback priorities

Find quick wins

quarterback quick-wins

Plan your day with time awareness

quarterback plan-day

LLM-Powered Setup (via MCP)

When using Quarterback as an MCP server, ask your LLM: *"Set up Quarterback for me"* — it will call the setup_quarterback tool, interview you conversationally about your business, goals, workflows, projects, constraints, and knowledge base (Playbook), then write all config files and database records in one shot. No manual YAML editing required.

MCP Server

Quarterback works with any MCP-compatible client — Claude Desktop, Claude Code, Cursor, Windsurf, Cline, OpenAI agents, and others. All 23 tools use standard MCP protocol (JSON-RPC over stdio) with no LLM-specific dependencies.

# Install with MCP support

pip install quarterback[mcp]

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{

"mcpServers": { "quarterback": { "command": "quarterback-server" } } }

Or for Claude Code (~/.claude/settings.json):

{

"mcpServers": { "quarterback": { "command": "quarterback-server" } } }

The same quarterback-server command works with any MCP client — just add it to your client's server configuration.

Then ask your LLM: *"What should I work on today?"* — it will use all 23 Quarterback tools to analyze your priorities.

Features

5-Factor Prioritization Engine

Every task is scored across five dimensions:

FactorWeightWhat it measures
Impact30%Task impact + project revenue/strategic value
Urgency25%Due date proximity + blocking status
Strategic25%Project priority + milestone status
Effort15%Inverted effort score (quick tasks score higher)
Quick Win5%High impact + low effort bonus
Advisory Document System

Analyze external articles, books, and advice against your organizational context:

# Import and auto-analyze an article

quarterback advisory-add --title "Growth Strategy" --url https://example.com/article

Review the analysis

quarterback advisory-view --id 1

Approve recommendations (optionally create tasks)

quarterback advisory-approve --id 1 --approve 1,3,5 --create-tasks

The analyzer checks every recommendation against your goals and constraints, flagging conflicts and synergies.

Agent Orchestration

Mark tasks for autonomous agent execution with configurable autonomy:

  • Draft: Agent creates a draft for your review
  • Checkpoint: Agent pauses at key decisions for approval
  • Autonomous: Agent runs to completion

Webhooks notify your automation layer (n8n, Zapier, custom) when tasks are ready.

Playbook — Knowledge Wiki

Playbook is Quarterback's compiled knowledge layer. It's an LLM-maintained markdown wiki that gives every session — local CLI, MCP, or autonomous agent — the same canonical context about your projects, decisions, and strategies.

The problem it solves: Without Playbook, each AI session starts fresh and re-derives your organizational context from sparse signals. Two sessions running the same query can produce different results because they reconstruct understanding independently. Playbook provides accumulated knowledge that all sessions read from.

How it works:

~/playbook/                          (or ~/.quarterback/playbook/)

├── CLAUDE.md # Schema — how the LLM reads/writes pages ├── raw/ # Drop zone for source material └── wiki/ ├── index.md # Master catalog — read this first ├── entities/ # Companies, products, clients, tools ├── concepts/ # Patterns, strategies, recurring themes ├── decisions/ # Decisions with rationale and alternatives ├── compiled/ # QB-compatible files for task scoring │ ├── goals.md # Read by QB's prioritization engine │ └── constraints.md # Read by QB's conflict detection └── log.md # Append-only operations record

Setup: Playbook is created automatically during quarterback setup (or the MCP setup wizard). The interview asks about your key entities, concepts, and decisions, then seeds initial wiki pages.

Without Playbook: Quarterback works exactly as before — reading goals and constraints from ~/.quarterback/org-context/ files. Playbook is opt-in.

With Playbook: Quarterback reads compiled/goals.md and compiled/constraints.md from Playbook first, falling back to org-context/ files if Playbook isn't initialized. Your LLM reads wiki/index.md for full organizational context.

# Check Playbook status

quarterback playbook status

Browse the index

quarterback playbook index

List pages by category

quarterback playbook list --category entities

Read a specific page

quarterback playbook read entities/my-product.md

Search across all pages

quarterback playbook search "budget"

Obsidian integration (optional): During setup, you can opt to configure Playbook as an Obsidian vault. Open the Playbook folder in Obsidian for graph visualization and visual editing. Install an Obsidian MCP server for programmatic access. No Obsidian dependency required — Playbook works as plain markdown files.

CI/CD Pipeline Integration

Quarterback's CLI and webhook system make it a natural fit for automated pipelines — update task status, log deliverables, and trigger downstream work without a human in the loop.

Direct CLI in pipelines

Add Quarterback commands to any CI/CD step. The CLI is stateless and scriptable:

# GitHub Actions example: auto-update task on deploy
  • name: Mark deploy task complete run: | pip install quarterback export QUARTERBACK_HOME=${{ runner.temp }}/.quarterback quarterback update 42 --status completed --notes "Deployed via CI, SHA: ${{ github.sha }}"
# After test suite passes, log results to a task
  • name: Report test results run: | quarterback update 38 --notes "Tests passed: 106/106, coverage 87%. Build #${{ github.run_number }}"
# Nightly: check for overdue deliverables and alert
  • name: Nightly priority check run: | quarterback alert-check quarterback priorities today --limit 5
Agentic CI/CD with webhooks

Register a webhook and let your automation layer react to task events in real time:

# Register a webhook pointing at your n8n/Zapier/custom endpoint

quarterback-server # MCP tools available, or use CLI:

# In your automation script: mark a task agent-ready after PR merge

import subprocess subprocess.run([ "quarterback", "update", "55", "--status", "completed", "--notes", f"PR #{pr_number} merged. Deployed to staging." ])

Use cases:

Pipeline eventQuarterback actionWhat happens
PR mergedupdate_task status=completedTask marked done, webhook fires to Slack
Deploy succeedsupdate_task with SHA + environment notesDeliverable tracked with audit trail
Nightly cronget_priorities + alert-checkTeam gets daily summary of what's overdue
Test suite failsadd_task with failure detailsBug auto-filed, linked to project
Sprint startsget_priorities + detect_conflictsSurface scheduling conflicts before work begins
Agent completes workupdate_agent_status status=completedWebhook notifies orchestrator, next task dispatched
Release taggedadvisory-add with release notesChangelog analyzed against project goals
Shared database across environments

Point multiple environments at the same Quarterback instance:

# All CI runners share one database via mounted volume or network path

export QUARTERBACK_HOME=/shared/quarterback

Or per-environment with migration

quarterback migrate /path/to/source

This lets your local CLI, CI pipelines, and MCP-connected agents all read and write to the same task graph — giving you a single source of truth across manual and automated workflows.

Time-Aware Planning
quarterback plan-day

Considers your working hours, lunch break, buffer time for meetings, and current time to suggest tasks that actually fit in your remaining day.

Configuration

Organizational Context

After quarterback init, run quarterback setup for an interactive wizard, or ask Claude to run the setup wizard via MCP. You can also manually configure your context in ~/.quarterback/org-context/:

~/.quarterback/org-context/

├── goals.md # Your strategic, workflow, and project goals ├── projects.yaml # Active projects with metadata ├── workflows.yaml # Groups of related projects └── constraints.md # Time, budget, and strategic boundaries

Example templates are included — copy from .example files and customize.

If you enable Playbook during setup, goals.md and constraints.md are auto-maintained from the wiki's compiled/ directory. You can still manually edit the org-context files — Playbook is additive, not required.

Alert Configuration

Configure notifications in ~/.quarterback/config/alerts.yaml:

  • Quiet hours (no notification

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx