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.
MCP server for async messaging between AI coding agents, enabling cross-harness and cross-machine communication with Slack-like semantics and mail-shaped delivery.
A comparative lab demonstrating MCP protocol evolution from stateful (2025-11-25) to stateless (2026-07-28) using a procure-to-pay agent, highlighting the implications for load balancing and session management.
A template repository for building Model Context Protocol (MCP) servers that enables developers to create interactive AI agents with real-time bidirectional communication capabilities through WebSocket and SSE endpoints.