™On its own, an AI model can only produce text. Tools are what let an agent act in the world: look something up, update a record, send a message.
What a tool is
A tool is a connection between the agent and some other system, with a clear description of what it does. For example:
- Search the web for current information
- Look up a customer in your CRM
- Read or add rows in a spreadsheet
- Check the calendar for free time slots
- Create a draft email or send a message
- Create an invoice in your accounting software
How an agent uses tools
The pattern is the same every time:
- The agent reads the request and decides a tool would help. "I need this customer's past orders."
- It asks to use the tool, with the details needed. "Look up orders for this email address."
- The tool does the action and sends the result back.
- The agent reads the result and decides what to do next. Use another tool, write an answer, or ask you.
The model never touches your systems directly. It asks, the tool acts, and the result comes back. That separation is what makes it possible to control what an agent can and can't do.
Reading versus doing
Tools fall into two groups, and the difference is important:
- Read tools look things up: search, check the calendar, read a record. If something goes wrong, nothing changes.
- Write tools change things: send emails, update records, create invoices, issue refunds. If something goes wrong, it happens for real.
A sensible rule: give agents read access freely, and write access carefully. For anything that reaches a customer or moves money, start with the agent drafting and a person approving.
Connecting tools is getting easier
Not long ago, every tool connection had to be custom built. Today, many apps offer ready-made connections, and a shared standard called the Model Context Protocol (MCP) lets AI tools plug into other software in a consistent way. For a small business, that means more of your existing apps can be connected to AI without custom development.