Agentic vision: Building visual intelligence with Amazon Bedrock and MCP servers

This article demonstrates how to build visual intelligence systems by integrating Amazon Bedrock, computer vision, and Model Context Protocol servers to enable AI agents to see, understand, and act on visual information.

• Combines Computer Vision, Strands Agents, and Model Context Protocol (MCP) to bridge perception, decision-making, and action in AI systems
• CV MCP server provides unified interface for image and video analysis using Amazon Rekognition, Bedrock Claude models, and Amazon Nova
• OpenSearch MCP server enables semantic image search using multimodal embeddings and natural language queries
• Streamlit UI allows users to upload images/videos and interact with AI agent for analysis, cropping, label detection, and background removal
• Three use cases: infrastructure-less CV pipelines, intelligent image cataloging with embeddings, and visual memory databases for contextual reasoning

The solution demonstrates how standardized protocols and serverless architectures make sophisticated computer vision applications accessible while reducing infrastructure complexity.