"UML" matching MCP servers:

A server that integrates trained Random Forest models with Bee Framework, enabling ReAct interactivity for AI tools and agents.

Transforms AI assistants into a full ML engineering environment for training and fine-tuning models across multiple backends (local GPU, Mistral, Together AI, OpenAI) and cloud providers (Lambda Labs, RunPod, SSH-accessible VPS), with dataset management, experiment tracking, cost estimation, and deployment to Ollama/Open WebUI.

Persistent memory for AI coding agents that stores and recalls preferences, decisions, and conventions via semantic similarity, with zero cloud dependencies and plug-and-play MCP integration for Claude Code.

Enables any AI agent to discover, query, and order from a restaurant's storefront via MCP tools. It handles menu lookup, modifier validation, and enforces a mandatory confirmation gate before payment, replacing the human-operated phone line.

Enables routing of ML tasks like chat, sentiment analysis, recommendations, and summarization to appropriate models through a dynamic YAML-based registry. Provides async FastAPI endpoints with streaming support, retry logic, and pluggable model architecture for scalable ML inference.

A comprehensive toolkit that enables automated interaction with Cisco Modeling Labs (CML) for creating network topologies, configuring devices, and managing lab environments.