Email Creation with AI Agents | Beefree SDK + PydanticAI MCP Showcase

Are you exploring agentic email design? We believe the future of content design means having AI agents and humans work seamlessly together to create content — and this simple demo app shows you how to create a design experience that does just that.

It connects the Beefree SDK (the most intuitive drag-and-drop email editor in the market) with a PydanticAI agent using the Model Context Protocol (MCP).

Here's what you can achieve:

• AI-Powered Email Design: Use natural language to create and modify email templates
• WYSIWYG Editor: Allow humans to easily edit drafts created by AI in the intuitive, drag-and-drop editor provided by the Beefree SDK

What powers this experience:

• Real-time Streaming: WebSocket-based streaming chat interface
• MCP Integration: Direct connection to Beefree's Streamble HTTP MCP Server.
• Modern Tooling: Built with uv for fast dependency management

Prerequisites

• Python 3.13+
• uv for package management (recommended)
• Beefree SDK account (If you already have an account, you can get your credentials here. If you're new to Beefree SDK, you can sign up for a free account.)
• OpenAI API key
• Beta access. Learn how to request access to the beta in our Beefree SDK MCP Server (Beta) documentation.

Quick start

1. Clone and install

# Clone the repository
git clone <repository-url>
cd beefree_mcp_example

# Install with uv
uv sync

2. Configure environment

Copy the example environment file and add your credentials:

cp .env.example .env

Edit .env with your credentials:

BEEFREE_CLIENT_ID=your_beefree_client_id
BEEFREE_CLIENT_SECRET=your_beefree_client_secret
BEEFREE_MCP_API_KEY=your_beefree_mcp_api_key
OPENAI_API_KEY=your_llm_api_key

3. Run the application

# With uv
uv run python main.py

The application will be available at http://localhost:8000

How it works

1. User Input: The user types a natural language request in the chat interface, such as a detailed description of the type of email campaign they'd like to draft.
2. Streaming Processing: PydanticAI agent processes using agent.run_stream()
3. MCP Execution: Direct HTTP calls to Beefree's MCP server modify the email template.
4. Real-time Updates: Streaming responses show the AI's thought process.
5. Editor Integration: Changes are reflected in the Beefree editor.

Resources

About the Beefree SDK

• Beefree SDK Documentation
• Beefree SDK MCP Server Documentation

About PydanticAI:

• PydanticAI Documentation
• PydanticAI MCP Integration

More resources:

• What's a Model Context Protocol?
• uv Documentation