Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
作者提供的说明(英文原文)
Strategic task prioritization and agent orchestration for multi-project operators
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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。
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。
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
注册名称已通过 GitHub 账户 bobbyrgoldsmith 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
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。
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)。
同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
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 Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
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。
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.
| Feature | Quarterback | TaskMaster AI | Shrimp Task Manager |
|---|---|---|---|
| Multi-project prioritization | 5-factor weighted engine | Single-project breakdown | Single-project |
| Advisory document system | Analyze articles against your goals | No | No |
| Agent orchestration | Autonomy levels + webhooks | No | No |
| Time-aware planning | Working hours, lunch, buffer time | No | No |
| Organizational context | Goals, constraints, workflows | No | No |
| Knowledge wiki (Playbook) | LLM-maintained wiki for cross-session consistency | No | No |
| Conflict detection | Cross-project scheduling conflicts | No | No |
| Standalone CLI | Full CLI without AI runtime | Requires AI | Requires AI |
| Cost | Free (MIT) | Free | Free |
# Install
pip install quarterback
quarterback init
quarterback setup
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
quarterback priorities
quarterback quick-wins
quarterback plan-day
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.
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.
Every task is scored across five dimensions:
| Factor | Weight | What it measures |
|---|---|---|
| Impact | 30% | Task impact + project revenue/strategic value |
| Urgency | 25% | Due date proximity + blocking status |
| Strategic | 25% | Project priority + milestone status |
| Effort | 15% | Inverted effort score (quick tasks score higher) |
| Quick Win | 5% | High impact + low effort bonus |
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
quarterback advisory-view --id 1
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.
Mark tasks for autonomous agent execution with configurable autonomy:
Webhooks notify your automation layer (n8n, Zapier, custom) when tasks are ready.
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
quarterback playbook index
quarterback playbook list --category entities
quarterback playbook read entities/my-product.md
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.
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.
Add Quarterback commands to any CI/CD step. The CLI is stateless and scriptable:
# GitHub Actions example: auto-update task on deploy
# After test suite passes, log results to a task
# Nightly: check for overdue deliverables and alert
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 event | Quarterback action | What happens |
|---|---|---|
| PR merged | update_task status=completed | Task marked done, webhook fires to Slack |
| Deploy succeeds | update_task with SHA + environment notes | Deliverable tracked with audit trail |
| Nightly cron | get_priorities + alert-check | Team gets daily summary of what's overdue |
| Test suite fails | add_task with failure details | Bug auto-filed, linked to project |
| Sprint starts | get_priorities + detect_conflicts | Surface scheduling conflicts before work begins |
| Agent completes work | update_agent_status status=completed | Webhook notifies orchestrator, next task dispatched |
| Release tagged | advisory-add with release notes | Changelog analyzed against project goals |
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
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.
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.
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.
Configure notifications in ~/.quarterback/config/alerts.yaml:
只显示了开头部分;其余内容请在仓库中阅读