经 AI Skill Hub 精选评估,开源MCP工具 获评「推荐使用」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.5 分,适合有一定技术背景的用户使用。
开源MCP工具 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。
开源MCP工具 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/dkships/pm-copilot
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"--mcp--": {
"command": "npx",
"args": ["-y", "pm-copilot"]
}
}
}
# 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 开源MCP工具 执行以下任务... Claude: [自动调用 开源MCP工具 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": {
"__mcp__": {
"command": "npx",
"args": ["-y", "pm-copilot"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
An MCP server that triangulates customer support tickets and feature requests to help PMs decide what to build next.
---
Real results: Analyzed 2,370 signals (2,136 support tickets + 234 feature requests) across 3 products in 55 seconds. Identified 16 themes, 15 convergent. Top priority: Booking & Scheduling (score: 134.6) — 629 tickets + 77 feature requests pointing at the same problem.
Read the full story: I built an MCP server that changed how I prioritize products — why I built this, how convergent signals work in practice, and what I learned building with Claude Code.
---
Raw ProductLift data access for browsing feature requests directly. Each request includes its public url.
| Parameter | Type | Default | Description |
|---|---|---|---|
portal_name | string | — | Filter to a specific portal |
include_comments | boolean | true | Include comments on each request |
status | string | — | Filter to requests with this status (case-insensitive), e.g. open, planned, completed |
git clone https://github.com/dkships/pm-copilot.git
cd pm-copilot
npm install
cp .env.example .env # Edit with your credentials
npm run build
A trimmed synthesize_feedback response at the default summary detail level. Values are illustrative; note the PII scrubbing applied to the customer quote.
{
"timeframe_days": 30,
"detail_level": "summary",
"portal_name": "all",
"fetched_at": "2026-06-01T16:00:00.000Z",
"pii_scrubbing_applied": true,
"pii_categories_redacted": ["email", "phone"],
"analysis": {
"total_data_points": 612,
"reactive_count": 548,
"proactive_count": 64,
"themes": [
{
"theme_id": "booking-scheduling",
"label": "Booking & Scheduling",
"category": "Core Product",
"priority_score": 87.1,
"convergent": true,
"signal_type": "convergent",
"reactive_count": 211,
"proactive_count": 19,
"evidence_summary": "230 signals (211 tickets, 19 requests). Convergent across both sources.",
"representative_quotes": [
"[Support ticket] \"Double-booked slots again after the timezone change — reach me at [EMAIL REDACTED]\"",
"[Feature request, 47 votes] \"Let me block buffer time between meetings\""
]
},
{
"theme_id": "billing-payment",
"label": "Billing & Payment",
"category": "Monetization",
"priority_score": 64.3,
"convergent": false,
"signal_type": "reactive",
"reactive_count": 188,
"proactive_count": 0,
"evidence_summary": "188 signals (188 tickets, 0 requests). Reactive only.",
"representative_quotes": [
"[Support ticket] \"Charged twice for the annual plan\""
]
}
],
"emerging_themes": [
{ "pattern": "csv export", "frequency": 12 }
],
"unmatched_count": 38
}
}
themes.config.json in the project root defines what themes to look for. Edit without rebuilding — loaded at runtime.
Ships with 16 data-driven themes across 9 categories. Add your own by appending to the themes array. Unmatched data points are analyzed for emerging patterns using bigram/trigram frequency detection.
- Changes aren't taking effect. The MCP client runs the compiled dist/. After editing source, run npm run build and restart the client (or the MCP server connection) to pick up new code. - No HelpScout mailbox named "…". Run list_sources to see the exact mailbox names, or pass the numeric mailbox_id directly. - No portal found with name "…" / portal missing. The portal must be configured in PRODUCTLIFT_PORTALS (or the single-portal env vars). Run list_sources to see configured portals.
该项目是一个开源的MCP工具,使用TypeScript编写,提供了客户支持票和功能请求的MCP服务器功能,值得关注。
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。
AI Skill Hub 点评:开源MCP工具 的核心功能完整,质量良好。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | pm-copilot |
| 原始描述 | 开源MCP工具:MCP server that triangulates customer support tickets and feature requests to he。⭐26 · TypeScript |
| Topics | ai-toolsclaudecustomer-feedbackhelpscoutmcptypescript |
| GitHub | https://github.com/dkships/pm-copilot |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-06-01 · 更新时间:2026-06-01 · 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