Using Docker Compose for AI Agent Development

This article walks through building a production-like local AI agent stack using Docker Compose, combining LiteLLM, Pinecone Local, Langfuse, MCP filesystem servers, and a FastAPI-based research agent into a reproducible development environment. The piece explains how to structure local distributed agent systems, proxy multiple model providers behind a unified API, run vector search locally, trace agent execution flows, expose tools through MCP, and preserve fast development iteration while staying close to production architecture.