Newsletter Generator

Newsletter Generator

Generates structured newsletters with 8 sections using AI and provides NLP analytics such as word count, reading time, sentiment, and keywords.

Category
访问服务器

README

AI-Powered Newsletter Generator (MCP)

1. Project Overview

This project is an AI-powered newsletter generation system built using the Model Context Protocol (MCP). It dynamically creates structured newsletters covering 8 distinct sections and provides automated NLP analytics (word count, reading time, sentiment, and keywords).

2. Architecture Explanation

The project is built on Node.js and uses the MCP SDK. It exposes two core tools:

  • generate_newsletter: Uses OpenAI's API to dynamically write content based on structured prompt templates.
  • analyze_newsletter: Uses local processing to parse the generated markdown, calculate word frequencies, estimate reading time, and score sentiment.

The MCP Server runs over stdio, allowing it to be integrated easily into local LLM clients like Claude Desktop, or run standalone via the CLI.

3. Prerequisites

  • Node.js (v18 or higher)
  • npm or yarn
  • Google Gemini API Key (optional but recommended for actual text generation)

4. Installation Steps

  1. Clone the repository or extract the files.
  2. Open your terminal in the project root.
  3. Run npm install to install the MCP SDK and dotenv.

5. Environment Variable Setup

  1. Copy .env.example and rename it to .env.
  2. Open .env and paste your Google Gemini API key:
    GEMINI_API_KEY=your_gemini_api_key_here
    

6. How to Start the MCP Server

To start the raw MCP server (which communicates via standard input/output):

npm start

(Note: Because it uses stdio, it will appear to hang. This is normal, as it is waiting for JSON-RPC messages. Press Ctrl+C to exit).

7. How to Generate Newsletter & 8. Run Analytics via CLI

To use the application manually as a standard Node app:

npm run cli

Follow the on-screen prompts to enter a topic. It will automatically generate the newsletter, save it to the /outputs folder, and print out analytics (saving the JSON to /analytics).

9. Example CLI Commands

npm install
npm run cli
# Topic: Quantum Computing in AI

10. How to Use with Claude (MCP Integration)

To use this server as a tool inside Claude Desktop:

  1. Open your Claude Desktop configuration file (e.g., claude_desktop_config.json).
  2. Add the following entry to your mcpServers block:
    {
      "mcpServers": {
        "newsletter-generator": {
          "command": "node",
          "args": ["/absolute/path/to/ai-newsletter-mcp/server/index.js"]
        }
      }
    }
    
  3. Restart Claude Desktop.
  4. Ask Claude: "Please generate a newsletter about Agentic Workflows using the generate_newsletter tool, and then analyze the result."

11. Future Improvements (For Final Year Project)

  • Database Integration: Connect MongoDB or PostgreSQL to track user historical generated newsletters and trends over time.
  • Advanced NLP: Replace heuristic sentiment analysis with a local HuggingFace model or an LLM call.
  • Web UI: Build a React.js or Next.js frontend to visualize the analytics using charting libraries like Recharts or Chart.js.
  • Email Dispatch: Integrate SendGrid or Nodemailer to automatically email the generated newsletter to a list of subscribers.

12. Automated Scheduling & Email Delivery

The project includes an automated workflow that generates, analyzes, and emails newsletters without manual intervention.

📧 Email Configuration

This system uses nodemailer. To send emails (e.g., via Gmail):

  1. Go to your Google Account > Security.
  2. Enable 2-Step Verification.
  3. Search for "App Passwords" and generate a new password for this app.
  4. Add the credentials to your .env file:
    EMAIL_USER=your-email@gmail.com
    EMAIL_PASS=your-16-char-app-password
    

(Security Note: Never commit your .env file or actual password to GitHub!)

⏰ Scheduler Configuration

Edit the config/schedulerConfig.json file to manage delivery:

Demo Mode (Every 5 minutes):

{ "mode": "interval", "intervalMinutes": 5 }

Production Mode (Daily at 8:00 AM):

{ "mode": "daily", "dailyTime": "08:00" }

🚀 How to Run the Scheduler

The scheduler boots up automatically when the MCP server runs. However, to run the scheduler independently for testing:

npm run scheduler

📋 Logging & Common Errors

All automated actions are logged inside the /logs directory.

  • SMTP Authentication Error: Check that you are using a Google App Password and not your standard login password.
  • Empty Output: Ensure your GEMINI_API_KEY is valid.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选