启动控制 是 AI Skill Hub 本期精选MCP工具之一。综合评分 8.0 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
启动控制 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
启动控制 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/jamesoleinik/launch-control
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"----": {
"command": "npx",
"args": ["-y", "launch-control"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 启动控制 执行以下任务... Claude: [自动调用 启动控制 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"____": {
"command": "npx",
"args": ["-y", "launch-control"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
A Product Launch Coordinator built with Microsoft Dataverse — from data model to agents to dashboard.
This repo is the companion to the Launch Control LinkedIn series by James Oleinik, Product Director for Microsoft Dataverse. Over 15 episodes (3/week for ~5 weeks), we build a complete product launch coordination system from scratch — and open-source every line of code.
pip install PowerPlatform-Dataverse-Clientnpm install -g @microsoft/dataverse```bash git clone https://github.com/jamesoleinik/launch-control.git cd launch-control cp .env.example .env
Full series index with links to each episode's README, preflight, and scripts: episodes/README.md.
| # | Episode | Hero capability |
|---|---|---|
| [1](episodes/ep-01-data-modeling/) | AI-Powered Data Modeling | Official Dataverse plugins for Copilot & Claude Code → first Dataverse tables |
| [2](episodes/ep-02-business-skills/) | Your Playbook & Ingestion | Business skills + mapping-driven CLI ingestion |
| [3](episodes/ep-03-staging-layer/) | Promoting the Staging Layer | Python + pandas; staging → unified |
| [4](episodes/ep-04-extending-and-enforcing/) | Extending & Enforcing the Model | Virtual entities (custom GitHub Issues) **+ a server-side business rule** the coding agent authors — guardrails every future agent must honor |
| [5](episodes/ep-05-custom-tools/) | Custom Tools | Custom API + two BYO MCP custom connectors registered with paconn |
| [6](episodes/ep-06-cowork-plugin/) | Cowork Plugin for Dataverse | Build & publish a Dataverse-aware Cowork (Teams) plugin |
| [7](episodes/ep-07-scout-autopilot/) | Microsoft Scout 🟡 | _(placeholder — blocked on Frontier preview access)_ |
| [8](episodes/ep-08-rbac/) | Roles & Reach | Four flat roles (Member / Owner / Viewer / Admin) over Eps 1–5 data + tools — same query, four lenses |
| [9](episodes/ep-09-the-agent/) | The Agent | Declarative Launch Coordinator + knowledge substrate |
| [10](episodes/ep-10-autonomous-agents/) | Autonomous Agents | Launch Sentinel — event-triggered autonomous agent |
| [11](episodes/ep-11-code-first-agent/) | The Code-First Agent | Same skills, different runtime — Python agent that pulls skills from Dataverse |
| [12](episodes/ep-12-the-dashboard/) | The Dashboard | Generative Power Apps page deployed via pac model genpage upload |
| [13](episodes/ep-13-copilot-just-knows/) | Copilot Just Knows | Native Copilot intelligence over Dataverse — no agent needed |
| [14](episodes/ep-14-agentic-admin/) | Agentic Administration | The management plane is agent-driven — capacity, audit, cleanup, blast-radius |
| [15](episodes/ep-15-full-orchestra/) | Full Orchestra + Your Turn | Six surfaces in 60 seconds + open-source CTA |
Each episode is also tagged in git: git checkout ep-09 to see the repo as it was at that episode's ship.
pip install -r scripts/python/requirements.txt
To verify any episode is set up correctly, run its preflight:
bash python episodes/ep-12-the-dashboard/preflight.py ```
高质量的MCP工具,具有自动化启动管理功能
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
经综合评估,启动控制 在MCP工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | launch-control |
| 原始描述 | 开源MCP工具:Launch Control — a 12-episode LinkedIn series building a launch-management syste。⭐8 · Python |
| Topics | mcpagentsai-agentspython |
| GitHub | https://github.com/jamesoleinik/launch-control |
| License | MIT |
| 语言 | Python |
收录时间:2026-06-13 · 更新时间:2026-06-13 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端