Most agent frameworks invent graphs, chains, and orchestration layers. But when you break it down retry, budget caps, memory, logging each one is just a (ctx, next) function. Same pattern web developers have used for 15 years. Where do you think the middleware model breaks down for agents?
We built agent-express around the idea that most agent failures aren't about the LLM they're about everything around it: cost runaway, context overflow, silent tool errors, no retry logic. Curious what's been the biggest pain point for others building agents for real workloads?
Agent Express is an open-source middleware framework for building AI agents in TypeScript.
If you've written Express.js middleware, you already know how to build agents. The model-tool-model loop in an agent is structurally identical to the request-response cycle in a web server — a context flows through composable (ctx, next) functions.
Three concepts: Agent, Session, Middleware. Five hooks. Built-in middlewares for budget tracking, guardrails, observability, memory compaction and others.
