mcp-openvision

# Product Context ## Problem Space Developers need simple access to vision AI capabilities but face common challenges: 1. **Complexity**: Working with vision AI models requires expertise in prompt engineering and API integration 2. **API Management**: Managing authentication and error handling for AI APIs is time-consuming 3. **Integration**: Adding vision capabilities to applications often requires custom code 4. **MCP Compatibility**: Ensuring vision tools properly follow MCP standards ## Solution Approach MCP OpenVision provides a simple solution by: 1. **MCP-Native Interface**: Offering standard MCP tools that follow protocol specifications 2. **Simplified Access**: Providing direct access to vision models through a consistent interface 3. **Essential Analysis Modes**: Including core analysis capabilities for common use cases 4. **Error Handling**: Implementing proper error handling for reliability 5. **Simple Configuration**: Offering basic configuration through environment variables ## User Experience Goals ### For Developers - **Quick Setup**: Get started with vision analysis in minutes - **Clear Documentation**: Find examples for all supported tools - **Reliability**: Trust that errors are handled properly - **MCP Compatibility**: Work seamlessly within the MCP ecosystem ## Key Use Cases 1. **Image Description**: Generate descriptions of images for applications 2. **Document Processing**: Extract text from images and documents 3. **Object Detection**: Identify objects in images 4. **Image Comparison**: Compare similarities and differences between images 5. **Accessibility**: Generate image descriptions for visually impaired users ## Value Proposition MCP OpenVision: 1. **Simplifies Integration**: Offers MCP-compliant tools for easy integration 2. **Handles Complexity**: Manages API communication and image encoding 3. **Provides Reliability**: Includes proper error handling and user-friendly messages 4. **Ensures Compatibility**: Follows MCP standards for ecosystem compatibility ## Future Considerations While focusing on essentials now, future enhancements could include: 1. **Additional Models**: Support for new vision models as they become available 2. **Enhanced Preprocessing**: Additional image optimization options 3. **Advanced Examples**: More complex integration examples These will only be considered after the core functionality is solid and user-tested, maintaining our focus on simplicity and reliability.