What happens inside an AI agent loop, and where MCP fits
The AI agent loop is simple: the model picks a tool, calls it, checks the result and goes again until the goal is met. Learn how tool calling works and why tool calling stops working well when your API has hundreds of endpoints. See how an MCP server (Model Context Protocol) lists only the tools your agent may call, and why max turns ends the loop with a hard stop.
What you will learn: - Trace one turn of the agent loop: goal, tools and a check - Set a goal and a max turns cap for every agent - Let an MCP server list the tools each agent may call - Stop a writer and reviewer loop before it burns your budget
#aiagents #mcp #agentloop
Chapters
- Trace one turn of the agent loop
- Set a goal and max turns
- Hit the limit of tools in a prompt
- Let MCP list the tools you may call
- Stop the loop at max turns
Transcript
Trace one turn of the agent loop
Okay, what exactly happens in an agent? If it is a small simple AI agent, it's basically a loop of well, you define that loop, how many maximum tans it needs to go and do that work. you define what is the goal, this is what success is, and you go in the loop and you find whether you can reach that success, or you come back to me. it's human in the loop, probably you might have heard this term quite a bit. if you are not able to reach the success because you are not able to make the end decision with verification of that output, then you come back. So you provide a task, and your model picks what needs to be done, and then it will pick what are all the tools you provide access to, and then it will call the tools, it will find the tools answer, and then it will go to the model and it will summarize the reply. So, in this case, this can be a single loop, this can be a multi-loop as well.
Set a goal and max turns
Depends on what is the goal you have provided. and you can define so it shouldn't go rogue, like it it retries, retries, retries, and without any end, that's wrong. So you need to define some of these boundaries, like what is the maximum turn it needs to go, and so on. This will work really well when you are having you know selected set of tools. I usually define like if you have five, six simple tools, which is very very dynamic data calling or API which is very specific to your domain, then this will work.
Hit the limit of tools in a prompt
But what if your API have hundreds of you know endpoints? Then it won't work very well. That is where MCP or some standardization will really
Let MCP list the tools you may call
help. Like you have AI agent and you call your MCP server. What tool I have access to? Instead of every tool I can call and the schema is coded inside the prompt, you will define, like, okay, what are all the tools I can call through the MCP and what are all the permission I have, and based on that, it will list down the tools. It won't list down entire tool list, but it will only list down selected setup. So if I am the manager, then it will list down certain permission. If I am the writer, then it will list down certain permission oriented tool list, and then you can call the system.
Stop the loop at max turns
There are many strategies which has been followed by followed by agentic loop. they they usually use exit codes, exit zero, exit one, exit two. Usually exit two means like you stop hard stop. Exit one means you know it's an error, but it's more of a warning. You can you can continue the loop, but it's still an error. You need to continue the agentic loop. You go and you do the loop. this can work very well when, for example, you you created a maximum turns, like number of times, three times you can try. Now, you have a writing agent, and the writing agent drafted one piece of content, and the reviewing agent gives a mark based on you know its own its own standard it have, and it will give the mark and it will say, like, okay, I will pass only the score which is above 95, but your score is under 85. So you need to go back and you know refine your draft and come back. Now you created maximum turns three times. The first time it is 85, second time it is 92, the third time also it fails 94. Then it needs to stop, it's a hard stop. Like you need to throw okay, maximum turns have reached, you need to stop the loop, otherwise, it will be looping and looping, and again you will be burning your budget. you don't know where the actual cost is going on.
This lesson comes with Pro, $149 a year: Get Pro. This lesson is cut from the free Lightning session Build a Multi-Agent System with MCP. The Live Labs build the same system with you, free, on Thursdays: see the Live Labs.