Agent middleware

Agentic AIArchitecture and orchestrationPublished By Simon Budziak

Agent middleware is code that intercepts an AI agent's execution before or after model calls, tool calls, or complete runs. It adds shared behavior such as authentication, logging, policy checks, retries, and result transformation without putting that logic inside every prompt or tool.

Microsoft Agent Framework exposes separate middleware layers for agent runs, chat calls, and function calls, as its middleware documentation explains. The placement determines which data and actions the middleware can see.

What belongs in agent middleware?

Cross-cutting controls belong there: request identifiers, LLM tracing, rate limits, input validation, and retry policy. Middleware keeps one rule consistent across every call path, while the agent harness decides how those layers surround the execution loop.

How is middleware different from guardrails?

Guardrails are policies or checks that constrain behavior. Middleware is one mechanism that can run them. Security middleware should validate proposed tool calls before execution and stop the chain on failure. It does not replace AI agent security, because credentials, isolation, and least privilege must also be enforced by systems the agent cannot rewrite.

Frequently asked questions

What can agent middleware inspect?

Depending on where it runs, middleware can inspect agent inputs and outputs, model requests, tool arguments and results, execution metadata, and errors.

Is middleware a security boundary?

It can enforce part of one, but only if all relevant calls pass through it and termination fails closed. Sandboxing and external authorization still belong outside the model process.

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