Supports configuration through environment variables for API keys and server settings
Provides a REST API interface for the MCP server, enabling clients to submit queries and receive meeting summaries
Implements Framer Motion for smooth animations and interactive experiences in the frontend
Generates structured Markdown reports for meeting summaries with proper formatting
Integrates with OpenAI to generate meeting summaries and structured Markdown reports from transcripts
Includes a React-based frontend for submitting transcripts and displaying AI-generated meeting summaries
Uses Selenium to automate browser interactions with Notebook LM for generating meeting summaries
Utilizes Tailwind CSS for styling the frontend interface with custom UI components
Uses Vite for frontend development environment and build tooling
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Meeting Summary Systemsummarize the transcript from our quarterly planning meeting"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
📄 MCP Meeting Summary System
此專案結合前端與後端,實現一套基於 AI 與多工具協同的會議摘要及問答系統。 前端搭配 React + Tailwind UI,後端使用 FastAPI + MCP 架構,支援串接 OpenAI 與 Selenium 自動生成會議摘要,提供高品質 Markdown 報告。
🛠 專案結構
.
📁 api/
├── main.py # FastAPI 入口點 + MCPClient
├── mcp_server.py # MCP 工具伺服器 (summarize_meeting add multiply等工具)
├── article_generator.py # Selenium + OpenAI 摘要核心邏輯
📁 frontend/
└── src/
├── components/ # 前端元件
│ └── ui/ # UI 元件
│ - button.tsx # 按鈕元件
│ - textarea.tsx # 文本輸入元件
│ - card.tsx # 卡片元件
├── frontend.tsx # 主要入口與介面元件
├── main.tsx # 前端入口點
├── vite.config.ts # Vite 配置(含別名設定)
└── tailwind.config.js # Tailwind CSS 設定
📁 api/utils/
└── logger.py # 日誌紀錄工具
├── transcripts/ # 儲存逐字稿與 Markdown 摘要
├── api/.env # 儲存 OpenAI API Key(已被 .gitignore 忽略)
├── pyproject.toml # Python 專案設定檔
├── README.md # 本說明文件Related MCP server: Meeting BaaS MCP Server
🧑💻 安裝方式(建議使用 uv)
# 安裝依賴(建議使用 uv)
uv pip install -r pyproject.toml
# 或使用 install 命令
uv pip install .
# 或使用 requirements.txt(如果你有產生的話)
uv pip install -r requirements.txt後端 (backend)
✅ 啟動 MCP 工具伺服器 - MODE 預設為 streamable-http
cd api
uv run ./mcp_server.py確保該檔案有註冊 @mcp.tool("summarize_meeting") 等功能,並支援 streamable-http, sse, stdio。
✅ 啟動 MCP Agent 問答介面
cd api
uv run ./main.py前端 (frontend)
- 使用 React + Vite 快速開發
- Tailwind CSS 設計 UI,包含 Button、Textarea、Card 等自訂元件
- Framer Motion 實現平滑動畫與互動體驗
- 功能:輸入問題或逐字稿,呼叫後端 API,顯示智能摘要或回答,並用打字機效果呈現結果啟動方式
cd front
npm install
npm run dev預設會在 http://localhost:5173 啟動開發伺服器。
API 文件
欄位 | 型別 | 說明 |
query | string | 使用者輸入內容,如逐字稿 |
POST http://localhost:8001/query
{
"query": "請幫我分析這份逐字稿內容..."
}回傳
{
"answer": "技術討論要點\n- ..."
}🧙♂️ 功能特色
🧠 多步推理 Agent:透過 GPT 工具選擇功能,自動呼叫 summarize_meeting 工具。
🕸 Selenium 操作 Notebook LM:用真實瀏覽器生成摘要。
📝 OpenAI Markdown 重整摘要:轉為結構化會議紀錄。
📦 支援 HTTP / SSE / Stdio 模式 MCP Client
🔐 .env 設定
建立 .env 檔案,內容如下:
OPENAI_API_KEY=your_key_here
MCP_MODE=streamable-http, sse, stdio
MAX_ITERATIONS=your_max_iterations_here
MAX_TOKENS=your_max_tokens_here
TEMPERATURE=your_temperature_here
REQUEST_TIMEOUT=your_timeout_here
MODEL=your_model_here
USER_DATA_DIR=your_data_dir_here
PROFILE_DIRECTORY=your_profile_directory_here
DIR=your_directory_here
MAX_INPUT_LENGTH=your_max_length_here或直接在 CLI 中執行:
export OPENAI_API_KEY=your_key_here
export MCP_MODE=streamable-http, sse, stdio
export MAX_ITERATIONS=your_max_iterations_here
export MAX_TOKENS=your_max_tokens_here
export TEMPERATURE=your_temperature_here
export REQUEST_TIMEOUT=your_timeout_here
export MODEL=your_model_here
export USER_DATA_DIR=your_data_dir_here
export PROFILE_DIRECTORY=your_profile_directory_here
export DIR=your_directory_here
export MAX_INPUT_LENGTH=your_max_length_here📎 TODO / 延伸規劃
整合新聞、論文與部落格自動爬取模組
支援一鍵生成分析摘要與可視化報表
MCP 工具可串接更多分析模組(如 trend 分析、風險評估)
📜 License
MIT License
聯絡作者
Steve Wang | 2025
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