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Agent Express
Middleware framework for AI agents — Express.js for LLMs
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.
I was building AI agents in TypeScript and kept noticing that every framework invents its own abstraction for things that are fundamentally middleware — intercept context, do something before/after the LLM call, pass control downstream.
Memory management? That's middleware that trims ctx.history before the model call. Budget caps? Middleware that checks state before next() and throws if cost exceeds a limit. Retry? Middleware that wraps next() in a loop with backoff.
So I built Agent Express with one core abstraction: (ctx, next) middleware — the same pattern Express.js, Koa, and Hono have used for a decade.
Here's a production-ready agent in 16 lines:
const agent = new Agent({
name: "weather",
model: "anthropic/claude-sonnet-4-6",
instructions: "You are a weather assistant.",
})
agent.use(guard.budget({ limit: 0.50 }))
agent.use(model.retry({ maxRetries: 2 }))
agent.use(tools.function({
name: "get_weather",
schema: z.object({ city: z.string() }),
execute: async ({ city }) => `72°F in ${city}`,
}))
Budget, retry, and tools are independent middleware that compose without knowing about each other. Same property that makes Express.js middleware powerful.
What it's NOT good for: Graph-based orchestration with conditional branching (use LangGraph) Full-stack AI platform with RAG, workflows, dashboard (use Mastra) React hooks for streaming UI (use Vercel AI SDK)
It's v0.1 — I'd love feedback on the API design, what middleware is missing, and what would make you try it.
“Middleware framework for AI agents — Express.js for LLMs”
Agent Express was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #103 on the daily leaderboard. 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.
On the analytics side, Agent Express competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Agent Express performed against the three products that launched closest to it on the same day.
Who hunted Agent Express?
Agent Express was hunted by Victor Kuzennyy. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Agent Express including community comment highlights and product details, visit the product overview.
Victor Kuzennyy
Hey Product Hunt! I'm the maker of agent-express.
I was building AI agents in TypeScript and kept noticing that every framework invents its own abstraction for things that are fundamentally middleware — intercept context, do something before/after the LLM call, pass control downstream.
Memory management? That's middleware that trims ctx.history before the model call. Budget caps? Middleware that checks state before next() and throws if cost exceeds a limit. Retry? Middleware that wraps next() in a loop with backoff.
So I built Agent Express with one core abstraction: (ctx, next) middleware — the same pattern Express.js, Koa, and Hono have used for a decade.
Here's a production-ready agent in 16 lines:
Budget, retry, and tools are independent middleware that compose without knowing about each other. Same property that makes Express.js middleware powerful.
What it's NOT good for:
Graph-based orchestration with conditional branching (use LangGraph)
Full-stack AI platform with RAG, workflows, dashboard (use Mastra)
React hooks for streaming UI (use Vercel AI SDK)
It's v0.1 — I'd love feedback on the API design, what middleware is missing, and what would make you try it.
Docs: https://agent-express.ai
GitHub: https://github.com/agent-express-ai/agent-express
Comparison article: https://agent-express.ai/blog/ag...