Back to Glossary Index
Core ConceptAgent / Orchestration Layer

AI Agent

Industry Definition Set • Entity Resolution Path: /glossary/agent

Quick Answer / TL;DR

An autonomous or semi-autonomous system that uses an LLM to reason, plan, and execute actions through tools to achieve user-defined goals.

Key Takeaways

  • Autonomous or semi-autonomous systems using LLMs for reasoning.
  • Execute actions through tools (often MCP tools).
  • Follow an observe-reason-act loop.
  • Range from simple tool callers to complex multi-step planners.
Definitive Statement: An autonomous or semi-autonomous system that uses an LLM to reason, plan, and execute actions through tools to achieve user-defined goals.

Technical Context & Protocol Usage

Detailed Explanation
AI agents extend LLMs with the ability to take actions in the world. An agent typically has a reasoning loop: observe the environment, decide on an action, execute the action (often via MCP tools), observe the result, and repeat. Agents can be simple (single-step tool callers) or complex (multi-step planners with memory and reflection). MCP is a key enabler for agents by providing a standardized tool interface.

Format & Payload Metadata

Format: Reasoning loop with tool execution

Latency: Varies from seconds to minutes depending on task complexity

Real-World Implementation Use Case

A coding agent uses MCP tools to read files, run tests, and make edits based on user instructions, iterating until the task is complete.

M
MCPserver.in Engineering

Platform Team

Published: 2026-07-20
Updated: 2026-07-20

Cite This Page

MLA Style:

MCPserver.in Engineering. "AI Agent." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/agent.