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vanman2024

Content & Image Generation MCP Server

by vanman2024
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Python
Hybrid

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!

Deploy to FastMCP Cloud Python 3.10+ FastMCP

Quick Links

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

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):

Service

Cost

Imagen 3 SD

$0.020 per image

Imagen 3 HD

$0.040 per image

Imagen 4 SD

$0.025 per image

Imagen 4 HD

$0.050 per image

Veo 2

$0.15 per second

Veo 3

$0.20 per second

Claude Sonnet

$0.003 per 1K tokens

Gemini Pro

$0.0005 per 1K tokens

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:

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

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.

This server cannot be installed

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security - not tested
A
license - permissive license
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quality - not tested

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