RichdaleAI MCP Server

A Model Context Protocol (MCP) server for AI image generation using RunPod's Stable Diffusion API.

Features

• Generate images using Stable Diffusion 3.5 Large model
• MCP-compatible server architecture
• Fast image generation with configurable parameters
• Support for various aspect ratios and style presets

Installation

From Source

# Clone the repository
git clone <repository-url>
cd MCP-API

# Install build dependencies
pip install build

# Build the package
python -m build

# Install locally
pip install dist/richdaleai_mcp-0.1.0-py3-none-any.whl

From TestPyPI

pip install --index-url https://test.pypi.org/simple/ richdaleai-mcp

Usage

From Terminal

Run the MCP server:

richdaleai-mcp

Set your RunPod API key in a .env file:

RUNPOD_API_KEY=your_api_key_here
RUNPOD_ENDPOINT_ID=your_endpoint_id_here

RUN From MCP Configuration

First install package.

pip install richdaleai-mcp

Configure the server in your mcp.json file:

{
  "mcpServers": {
    "richdaleai_mcp": {
      "command": "python",
      "args": ["-m", "richdaleai_mcp"],
      "env": {
        "RUNPOD_API_KEY": "your_runpod_api_key_here",
        "RUNPOD_ENDPOINT": "https://api.runpod.ai/v2/your_endpoint_id/runsync",
        "IMAGE_STORAGE_DIRECTORY": "/path/to/image/storage"
      }
    }
  }
}

Environment Variables:

• RUNPOD_API_KEY: Your RunPod API key
• RUNPOD_ENDPOINT: RunPod endpoint URL for image generation
• IMAGE_STORAGE_DIRECTORY: Directory to store generated images

Development

Dependencies

• Python 3.11+
• fastmcp
• requests
• python-dotenv

Building

python -m build

Testing

# Install in development mode
pip install -e .

License

This project is licensed under the GNU Affero General Public License v3 - see the LICENSE file for details.

API Response Example

{"delayTime":1036,"executionTime":8805,"id":"sync-2f895f28-d6be-4264-a978-657041fe1754-e1","output":{"images":["data:image/png;base64,iVBORw0KJwFmxrbRK5CYII="],"images_info":{"count":1,"seed":15121496791610440000,"shape":"torch.Size([1, 3, 1024, 1024])"},"input_parameters":{"batch_count":1,"batch_size":1,"build_dynamic_shape":false,"build_static_batch":true,"denoising_steps":30,"framework_model_dir":null,"guidance_scale":3.5,"height":1024,"low_vram":false,"max_sequence_length":256,"negative_prompt":"","num_warmup_runs":0,"prompt":"A simple blue circle on a white background","seed":null,"use_cuda_graph":false,"version":"3.5-large","width":1024},"job_id":"sync-2f895f28-d6be-4264-a978-657041fe1754-e1","message":"Images generated successfully in 7631.47ms","status":"success"},"status":"COMPLETED","workerId":"gz8euubmvp42dr"}