Agents & MCP
AI agent
An AI system that doesn't just answer once but works toward a goal over multiple steps — planning, calling tools, reacting to results, and looping until done. Because an agent can make many calls per task, it can spend far more than a single prompt, and it spends without a human watching each step.
Example
You ask an agent to "research our top five competitors and draft a summary." It makes 40 model calls and a dozen web fetches on its own before returning one document. The spender is no longer a person clicking send — it's software in a loop.
Related terms
Subagent
A smaller agent spawned by a parent agent to handle a piece of the work. Subagents let one task fan out into many, which is powerful — and a spend-attribution challenge, because their cost needs to roll back up to the agent that launched them.
Agent identity
Giving an autonomous agent its own distinct identity — its own key, budget, and record — rather than having it act under a human's credentials. Without it, an agent's spend and actions are indistinguishable from the person who launched it.
Tool call
A single action an agent takes to use an external capability — query a database, search the web, run a function — as opposed to just generating text. Each tool call is a step where the agent reaches outside the model.
MCP (Model Context Protocol)
An open standard for how AI agents connect to external tools and data sources in a consistent way — a common "plug" so any compatible agent can use any compatible tool. It's how modern agents reach beyond the model to your systems.