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olgasafonova/productplan-mcp-server

olgasafonova/productplan-mcp-server

🏎️ ☁️ - Query ProductPlan roadmaps, OKRs, ideas, launches and timeline data
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add productplan-mcp-server -- npx -y productplan-mcp-server
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
3 ★ · olgasafonova/productplan-mcp-server · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 3 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 olgasafonova/productplan-mcp-server;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

ProductPlan MCP Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**Talk to your roadmaps using AI.** Ask questions, create ideas, check OKR progress, and manage launches through natural conversation with Claude, Cursor, or other AI assistants.
What can you do with this?
Instead of clicking through ProductPlan's interface, just ask:
> "What's on our Q1 roadmap?"
> "Show me all objectives that are behind schedule"
> "Create a new idea for mobile app improvements"
> "What launches are coming up this month?"
> "List all ideas tagged 'customer-request'"
> "Color every eFormidling bar with the Customer satisfaction legend"
> "Move these ten bars to the Platform lane and tag them Q3"
The AI fetches your real ProductPlan data and responds in seconds. Changes to many bars go through one validated call: every bar is checked before anything is written, and you can ask for a dry run first.
Who is this for?
- **Product Managers** who want faster access to roadmap data
- **Team leads** who need quick status updates without context-switching
- **Anyone using AI assistants** (Claude, Cursor, etc.) who wants ProductPlan integrated into their workflow
No coding required. You'll copy a file and paste some settings.
---
Quick start (5 minutes)
Step 1: Get your ProductPlan API token
1. Log into ProductPlan
2. Go to **Settings** → **API** (or visit this link directly)
3. Copy your API token
Step 2: Download the app
Go to the Releases page and download the right file for your computer:
| Your Computer | Download This |
|---------------|---------------|
| Mac (M1, M2, M3, M4) | productplan-darwin-arm64 |
| Mac (Intel) | productplan-darwin-amd64 |
| Windows | productplan-windows-amd64.exe |
| Linux | productplan-linux-amd64 |
**On Mac/Linux**, open Terminal and run these two commands (replace the filename with what you downloaded):
You'll be asked for your password. This is normal.
**On Windows**:
1. Create a folder for the binary (if it doesn't exist):
2. Move the downloaded .exe to that folder and rename it:
3. Use the full path C:\Tools\productplan.exe in your AI assistant config (shown in Step 3)
> **Note**: You can skip adding to PATH. Just use the full file path in your configuration.
Step 3: Connect to your AI assistant
Pick the tool you use:
Claude Desktop (click to expand)
1. Find your config file:
- **Mac**: ~/Library/Application Support/Claude/claude_desktop_config.json
- **Windows**: %APPDATA%\Claude\claude_desktop_config.json
2. Open it in any text editor and add this (replace your-token with your actual API token):
**Mac/Linux:**
**Windows:**
3. Restart Claude Desktop
Claude Code (Terminal)
Add to your config file:
- **Mac/Linux**: ~/.claude.json
- **Windows**: %USERPROFILE%\.claude.json
**Mac/Linux:**
**Windows:**
Cursor
1. Open Cursor
2. Go to **Settings** → **MCP Servers**
3. Add this configuration:
**Mac/Linux:**
**Windows:**
> **Windows users**: Use double backslashes (\\) in the path. This is required because backslash is an escape character in JSON.
VS Code + Cline
1. Install the Cline extension
2. Open VS Code settings (JSON) and add:
**Mac/Linux:**
**Windows:**
VS Code + Continue
1. Install the Continue extension
2. Add to your config file:
- **Mac/Linux**: ~/.continue/config.json
- **Windows**: %USERPROFILE%\.continue\config.json
**Mac/Linux:**
**Windows:**
n8n (Workflow Automation)
1. Set environment variable on your n8n instance:
2. Add an **MCP Client** node to your workflow
3. Configure:
- **Command**:
- Mac/Linux: /usr/local/bin/productplan
- Windows: C:\Tools\productplan.exe
- **Environment Variables**: PRODUCTPLAN_API_TOKEN=your-token
4. Connect to an **AI Agent** node
Example workflow: Slack Trigger → AI Agent (with MCP Client) → Slack Response
Step 4: Start asking questions
Open your AI assistant and try:
- "List my ProductPlan roadmaps"
- "What bars are on roadmap [name]?"
- "Show me our OKRs"
- "What ideas are in discovery?"
---
Real-world use cases
Morning standup prep
> "Summarize what changed on our Product Roadmap in the last week"
Stakeholder updates
> "List all Q1 objectives and their progress"
来源
awesome · https://github.com/olgasafonova/productplan-mcp-server
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