What is tool calling?
Tool calling is how an AI agent takes action instead of only producing text. The model is given a set of tools — like search, a database query, or sending a message — and decides when to call one, with what inputs. The tool runs, returns a result, and the agent continues.
Tool calling is the mechanism that turns a language model from a text generator into something that gets work done. Without tools, a model can only talk about a task. With tools, it can actually do it.
How tool calling works
- The agent is given a list of tools, each with a description and expected inputs.
- For the current step, the model decides whether a tool is needed and which one.
- It calls the tool with specific inputs; the tool runs and returns a result.
- The agent reads the result and continues — often calling more tools until the task is done.
Standards like the Model Context Protocol make these tools reusable across agents and vendors, so you connect a system once.
Tool calling in Oido
Oido gives agents built-in tools plus any tool you connect through integrations and MCP. You control which tools each AI employee can use, and agents call them automatically as a task requires — on whichever model provider you run.
Frequently asked
Tool calling is the agent deciding to use a tool. MCP is a standard way to connect those tools so any compatible agent can use them. Tool calling is the action; MCP is the plumbing that makes tools reusable across agents and providers.
Each tool comes with a name and description of what it does and what inputs it needs. The model reads these and picks the right one for the current step — the same way a person reads a menu of options.
Yes, if you allow it. Tools can be read-only (look something up) or able to act (update a record, send an email). Good platforms let you control which tools an agent can use and add approval steps.