Content & Image Generation MCP Server

AI-powered content and image generation FastMCP server with Google Imagen 3/4 image generation, Veo 2/3 video generation, and Claude/Gemini content generation.

Production Ready: Deploy to FastMCP Cloud in 5 minutes!

Quick Links

• 5-Minute Deployment Guide - Get started fast

• Complete Deployment Guide - Detailed instructions

• Deployment Checklist - Ensure nothing is missed

Features

Tools

1. health_check - Server health and monitoring

   • Verify server health and API connectivity

   • Check service availability (Google AI, Anthropic)

   • Output directory validation

   • Perfect for monitoring deployments

2. generate_image_imagen3 - Generate high-quality marketing images

   • Google Imagen 3/4 integration

   • Multiple aspect ratios (1:1, 16:9, 9:16, 4:3, 3:4)

   • 1K and 2K resolution options

   • Negative prompts for better control

   • Production-ready with error handling

3. batch_generate_images - Generate multiple images efficiently

   • Batch processing for campaigns

   • Cost tracking across multiple images

   • Consistent quality and style

   • Detailed success/failure reporting

4. generate_video_veo3 - Create marketing videos

   • Google Veo 3 integration

   • Customizable duration (4, 6, 8 seconds)

   • 720p and 1080p resolution

   • Native audio generation

   • Cost estimation per second

5. generate_marketing_content - AI-powered copywriting

   • Multiple content types (social posts, blog intros, ad copy, email subjects, product descriptions)

   • Choice of Claude Sonnet 4 or Gemini 2.5 Flash Image

   • Tone customization (professional, casual, enthusiastic, formal)

   • Length control (short, medium, long)

   • Optional hashtag generation

6. calculate_cost_estimate - Campaign budget planning

   • Detailed cost breakdown by service

   • Support for multiple models

   • Per-resource pricing

   • Campaign planning assistant

Resources

• config://pricing - Current pricing for all services

• config://models - Available AI models and capabilities

Prompts

• campaign_planner - Interactive campaign planning assistant

• image_prompt_enhancer - Optimize image generation prompts

Prerequisites

• Python 3.10+ (required for FastMCP)

• uv or pip package manager

• Google Cloud Account with Vertex AI API enabled

• Anthropic API Key (for Claude content generation)

• Google AI API Key (for Gemini content generation)

Installation

1. Clone or Navigate to Project

cd marketing-automation

2. Create Virtual Environment

Using uv (recommended):

uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

Or using standard Python:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install Dependencies

Using uv:

uv pip install -e .

Or using pip:

pip install -e .

For development with testing tools:

uv pip install -e ".[dev]"

Configuration

1. Set Up Google Cloud

1. Create a Google Cloud project at https://console.cloud.google.com

2. Enable the Vertex AI API

3. Create a service account with Vertex AI permissions

4. Download the service account key JSON file

5. Set the path to your credentials file

2. Get API Keys

• Anthropic: Get your API key from https://console.anthropic.com

• Google AI: Get your API key from https://makersuite.google.com/app/apikey

3. Create Environment File

Copy the example environment file:

cp .env.example .env

Edit .env with your configuration:

# Google Cloud Configuration
GOOGLE_CLOUD_PROJECT=your-project-id
GOOGLE_CLOUD_LOCATION=us-central1
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-key.json

# Anthropic API Configuration
ANTHROPIC_API_KEY=sk-ant-api03-your-key-here

# Google Generative AI (Gemini)
GOOGLE_API_KEY=your-google-ai-api-key

# Server Configuration
MCP_SERVER_NAME=Marketing Automation
MCP_SERVER_PORT=8000

Important: Never commit the .env file with real credentials!

Usage

Local Development (STDIO for Claude Desktop)

Run the server in STDIO mode:

python server.py

Or using FastMCP CLI:

fastmcp run server.py

HTTP Server for Deployment

Run the server in HTTP mode:

python server.py --http

The server will start on http://0.0.0.0:8000

Claude Desktop Integration

Add to your Claude Desktop config file:

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

{
  "mcpServers": {
    "marketing-automation": {
      "command": "python",
      "args": [
        "/absolute/path/to/marketing-automation/server.py"
      ],
      "env": {
        "GOOGLE_CLOUD_PROJECT": "your-project-id",
        "GOOGLE_CLOUD_LOCATION": "us-central1",
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/service-account-key.json",
        "ANTHROPIC_API_KEY": "sk-ant-api03-your-key",
        "GOOGLE_API_KEY": "your-google-ai-key"
      }
    }
  }
}

Note: Use absolute paths for both the server script and credentials file.

Example Usage

Generate a Marketing Image

# Via Claude Desktop or MCP client
generate_image_imagen3(
    prompt="Professional product photography of a luxury watch, white background, studio lighting, high detail, commercial quality",
    aspect_ratio="1:1",
    quality="hd"
)

Batch Generate Images for Campaign

batch_generate_images(
    prompts=[
        "Modern tech startup office, collaborative workspace, natural light",
        "Smartphone app interface, clean design, user-friendly",
        "Happy customers using product, lifestyle photography"
    ],
    quality="hd",
    aspect_ratio="16:9"
)

Generate Marketing Copy

generate_marketing_content(
    content_type="social_post",
    topic="Launch of new AI-powered analytics platform",
    tone="enthusiastic",
    length="medium",
    model="claude",
    include_hashtags=True
)

Estimate Campaign Costs

calculate_cost_estimate(
    images_hd=10,
    images_sd=20,
    video_seconds=30,
    content_pieces=15
)

Pricing

Approximate costs (as of October 2025):

Use calculate_cost_estimate tool for detailed budget planning.

Output Directory

Generated content is saved to the output/ directory:

• Images: output/imagen3_YYYYMMDD_HHMMSS.png

• Videos: output/veo3_YYYYMMDD_HHMMSS.mp4

Security Best Practices

1. Never hardcode API keys - Always use environment variables

2. Use .env for local development - Never commit .env to git

3. Rotate credentials regularly - Especially for production use

4. Set up cost alerts - Monitor Google Cloud and Anthropic usage

5. Use service accounts with minimal permissions - Follow principle of least privilege

Deployment

FastMCP Cloud (Recommended)

Quick Deployment: Deploy to production in 5 minutes!

1. Visit: https://cloud.fastmcp.com

2. Sign in with GitHub

3. Create new project:

   • Repository: vanman2024/content-image-generation-mcp

   • Entrypoint: server.py:mcp

4. Set environment variable: GOOGLE_API_KEY=<your-key>

5. Deploy

Your server will be available at:

https://content-image-generation-mcp.fastmcp.app/mcp

Full Documentation:

• Quick Start Guide - 5-minute deployment

• Complete Deployment Guide - Detailed instructions

• Deployment Checklist - Step-by-step checklist

Validation (optional but recommended):

./scripts/validate-deployment.sh

Production Features

Your deployment includes:

• ✅ Structured logging with configurable levels

• ✅ Health check endpoint for monitoring

• ✅ Error handling and API validation

• ✅ Automatic redeployment on git push

• ✅ Zero-downtime deployments

• ✅ Cost tracking and estimation

IDE Integration

After deploying, connect from your IDE:

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "content-image-generation": {
      "url": "https://content-image-generation-mcp.fastmcp.app/mcp",
      "transport": "sse"
    }
  }
}

Cursor (.cursor/mcp_config.json):

{
  "mcpServers": {
    "content-image-generation": {
      "url": "https://content-image-generation-mcp.fastmcp.app/mcp",
      "transport": "sse"
    }
  }
}

Alternative Deployment Options

Local Development (STDIO):

python server.py
# or
fastmcp run server.py

HTTP Server:

python server.py --http
# Server runs on http://0.0.0.0:8000

Docker:

FROM python:3.10-slim
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
ENV GOOGLE_API_KEY=""
CMD ["python", "server.py", "--http"]

Build and run:

docker build -t content-image-generation-mcp .
docker run -p 8000:8000 -e GOOGLE_API_KEY=your_key content-image-generation-mcp

Troubleshooting

Import Errors

# Reinstall dependencies
uv pip install --force-reinstall -e .

Google Cloud Authentication

# Verify credentials
gcloud auth application-default login

# Check project
gcloud config get-value project

API Key Issues

# Verify environment variables are loaded
python -c "import os; from dotenv import load_dotenv; load_dotenv(); print(os.getenv('ANTHROPIC_API_KEY'))"

Development

Run Tests

pytest tests/

Code Formatting

black server.py
ruff check server.py

Add New Tools

Follow FastMCP patterns:

@mcp.tool()
def my_new_tool(param: str) -> Dict[str, Any]:
    """Tool description for LLM"""
    return {"success": True, "result": param}

Resources

• FastMCP Documentation: https://gofastmcp.com

• Google Vertex AI: https://cloud.google.com/vertex-ai/docs

• Anthropic Claude: https://docs.anthropic.com

• Google Gemini: https://ai.google.dev

Support

For issues or questions:

1. Check the FastMCP documentation

2. Review Google Cloud Vertex AI docs

3. Verify API credentials and quotas

4. Check the output/ directory for generated files

License

Apache 2.0

Built with FastMCP 2.13.0 - The fast, Pythonic way to build MCP servers.