AI and ML MCP servers let Claude and other AI assistants orchestrate machine learning pipelines, call other AI models, generate embeddings, run image recognition, and interact with vector stores — effectively becoming an AI that coordinates other AIs. Researchers and ML engineers use them to chain models together, compare outputs from different providers, or inject semantic search into a broader workflow. This category is growing rapidly as the MCP ecosystem moves toward multi-agent architectures.