kumarAbhishek2004/Ai_Newletter

🤖 AI Newsletter Automation MCP Server

📖 What is MCP?

MCP (Model Context Protocol) is a revolutionary framework that allows AI assistants like Claude to interact with external tools and services through standardized interfaces. Think of it as a "plugin system" for AI - it enables Claude to:

• 🔍 Search the web and fetch real-time data
• 📁 Access and manage files in Google Drive
• 📧 Read and send emails via Gmail
• 🛠️ Execute custom functions and APIs

This MCP server specifically provides Claude with tools to automate the entire AI newsletter creation process - from research to publication.

✨ Features

🔍 Research Phase

• arXiv Papers: Fetch latest AI research papers with summaries
• GitHub Trending: Discover trending AI repositories and projects
• Product Hunt: Track new AI tools and products
• Twitter Trends: Capture viral AI discussions and tweets
• Gmail Feedback: Analyze reader feedback and engagement
• Past Newsletters: Learn from previous newsletter performance

✍️ Editing Phase

• Smart Content Organization: Automatically categorize and prioritize content
• Draft Creation: Generate structured newsletter drafts
• Content Validation: Check completeness and quality
• Text Preview: Quick review before publishing

🎨 Design Phase

• HTML Generation: Beautiful, responsive email templates
• Multi-Format Export: HTML, Markdown, and JSON formats
• Google Drive Integration: Auto-save to cloud storage
• Mobile-Friendly: Responsive design for all devices

🚀 Quick Start with FastMCP Cloud

Option 1: Use Our Hosted Server (Recommended)

No installation required! Connect directly to our hosted MCP server:

Step 1: Open Claude Desktop Configuration

• Mac: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Step 2: Add This Configuration

{
  "mcpServers": {
    "ai-newsletter": {
      "url": "https://linguistic-chocolate-grouse.fastmcp.app/mcp"
    }
  }
}

Step 3: Restart Claude Desktop

Close and reopen Claude Desktop. The AI Newsletter tools will now be available!

Step 4: Start Using It

Open a conversation with Claude and try:

Help me research and create this week's AI newsletter

Claude will automatically use the newsletter tools to gather content, organize it, and create a draft for you!

🛠️ Local Installation (For Developers)

Prerequisites

• Python 3.8 or higher
• Google Cloud Project with OAuth credentials
• (Optional) API keys for Twitter, Product Hunt, GitHub

Step 1: Clone the Repository

git clone https://github.com/kumarAbhishek2004/Ai_Newletter.git
cd Ai_Newletter

Step 2: Install Dependencies

pip install -r requirements.txt

Step 3: Set Up Environment Variables

Create a .env file in the project root:

# Required: Google OAuth (for Drive & Gmail)
GOOGLE_CLIENT_ID=your_client_id_here
GOOGLE_CLIENT_SECRET=your_client_secret_here
GOOGLE_REFRESH_TOKEN=your_refresh_token_here

# Optional: Newsletter folder in Google Drive
NEWSLETTER_FOLDER_ID=your_folder_id_here

# Optional: External APIs
GITHUB_TOKEN=your_github_token_here
PRODUCT_HUNT_API_KEY=your_producthunt_key_here
TWITTER_BEARER_TOKEN=your_twitter_token_here

Step 4: Run the Server Locally

python main.py

Step 5: Configure Claude Desktop for Local Server

{
  "mcpServers": {
    "ai-newsletter": {
      "command": "python",
      "args": ["/path/to/your/Ai_Newletter/main.py"]
    }
  }
}

📋 Usage

Quick Start Workflow

Once connected, simply ask Claude:

For Complete Newsletter Creation:

Create this week's AI newsletter covering the latest papers, GitHub projects, and products

For Specific Research:

Search arXiv for papers about large language models from the past week

For Organization:

Organize my newsletter content into sections and prioritize the most important items

For Publishing:

Generate an HTML newsletter and save it to my Google Drive

Available Tools

Research Tools

• fetch_all_research() - Batch fetch from all sources
• search_arxiv_papers() - Get latest research papers
• fetch_github_trending() - Find trending repositories
• search_product_hunt() - Discover new AI products
• fetch_twitter_trends() - Track viral conversations
• fetch_past_newsletters() - Analyze previous issues
• scan_gmail_feedback() - Read reader responses

Editing Tools

• create_newsletter_draft() - Generate structured draft
• organize_content_sections() - Prioritize content
• validate_newsletter_content() - Quality check
• preview_newsletter() - Text preview

Publishing Tools

• generate_html_newsletter() - Create HTML version
• save_to_drive() - Upload to Google Drive
• export_newsletter() - Export in multiple formats

Example Workflow

Conversation with Claude:

You: "Help me create this week's AI newsletter"

Claude: Uses fetch_all_research() to gather content from arXiv, GitHub, Product Hunt, etc.

Claude: "I've gathered 10 research papers, 8 trending repos, and 5 new products. Here's what I found..."

You: "Great! Now organize this into sections and create a draft"

Claude: Uses create_newsletter_draft() to organize content

Claude: "I've created a draft with 5 sections. Would you like me to generate the HTML version?"

You: "Yes, and save it to Google Drive"

Claude: Uses generate_html_newsletter() and save_to_drive()

Claude: "Done! Your newsletter has been saved to Google Drive. Here's the preview..."

⚙️ Configuration

Google OAuth Setup

1. Go to Google Cloud Console
2. Create a new project
3. Enable Google Drive API and Gmail API
4. Create OAuth 2.0 credentials
5. Generate refresh token using OAuth playground
6. Add credentials to .env file

Optional API Keys

• GitHub: Create personal access token
• Product Hunt: Get API key
• Twitter: Apply for developer access

📊 Sample Output

Text Preview

============================================================
 AI Newsletter #4
Issue #4| November 02, 2025
============================================================

📊 CONTENT SUMMARY:
- Papers: 10
- GitHub Repos: 8
- Products: 5
- Tweets: 3

🎯 BIG STORY:
Breakthrough in Multi-Modal AI Reasoning

📄 TOP PAPERS:
1. Efficient Attention Mechanisms for Transformers
2. Zero-Shot Learning in Vision-Language Models
3. Reinforcement Learning for Real-World Robotics

HTML Newsletter

• 📱 Mobile-responsive design
• 🎨 Modern, clean aesthetic
• 🔗 Clickable links to all sources
• 📊 Visual badges and metrics
• 💌 Professional email format

📝 License

This project is licensed under the MIT License - see the file for details.

👥 Author

Kumar Abhishek

ML Engineer & Full Stack Developer

🎓 BTech ECE @ IIIT Una
💡 Specializing in AI/ML, GenAI, and Web Development

📞 Contact & Support

• Email: abhishek.kr0418@gmail.com
• GitHub: kumarAbhishek2004
• LinkedIn: kumar-abhishek-6b5828288
• Issues: Report Bug

🙏 Acknowledgments

• FastMCP - Simplified MCP server creation
• Anthropic - Claude AI and MCP framework
• arXiv API - Research paper access
• GitHub API - Repository data
• Product Hunt API - Product discovery