mcp-openvision

# Project Brief: MCP OpenVision ## Project Overview MCP OpenVision is a Model Context Protocol (MCP) server that provides image analysis capabilities through OpenRouter's vision-capable AI models. It enables developers to easily integrate advanced vision analysis into their applications without having to directly manage API connections, image encoding, or prompt engineering. ## Core Requirements 1. Provide a simple, MCP-compliant interface for image analysis 2. Connect to OpenRouter's API to access vision models 3. Support essential analysis modes (general description, text extraction, etc.) 4. Handle image encoding and API communications reliably 5. Follow MCP SDK standards and best practices ## Technical Goals 1. Create a focused, well-tested MCP server implementation 2. Implement basic error handling for reliability 3. Provide simple configuration options 4. Include essential image preprocessing utilities 5. Create clear documentation with examples ## Target Audience - Developers building applications requiring image analysis - Users of the MCP ecosystem needing vision capabilities - Data scientists working with image datasets ## Success Criteria 1. All tools function correctly with proper error handling 2. Documentation is clear and comprehensive 3. Package is easy to install and configure 4. Perfect compliance with MCP SDK patterns 5. Tool responses are helpful and user-friendly ## Timeline - Phase 1 (2 weeks): Core essentials - error handling, configuration, tests, MCP compliance - Phase 2 (2 weeks): User experience - client helpers, image preprocessing, documentation ## Resources - OpenRouter API for accessing vision models - MCP Python SDK for server implementation - Python standard libraries for core functionality