liveBook · Manning

List_tools

As explained in Building Reliable AI Systems

An MCP server endpoint that returns machine-readable descriptions of its available tools and their inputs.

The `/tools/list` endpoint lets an MCP server declare its available tools. It returns machine-readable descriptions including each tool’s name, input parameters, output format, and purpose. section 7.6.1

When an MCP server is added to the tools array, the OpenAI runtime queries the endpoint at the start of the conversation and loads the schemas into context. The model can then reason about the tools like native functions, without manually supplying schemas inline. section 7.6.1

Describing available actions

A server might expose semantically named actions such as “search for a product” and “check availability.” section 7.6.1

Figure 7.2 How AI discovers and uses MCP tools. When tools are registered on the server, the AI model can automatically discover, reason about, and invoke them.
figure

Shows the flow from registering server tools to model discovery and invocation. section 7.6.1

How Building Reliable AI Systems covers it

How deep it goes
Defines returned fields and traces schema loading into conversation context, without detailing endpoint implementation.
Examples
Uses product search and availability checks to illustrate semantically named tools.
What you can do after
Understand how an MCP server exposes tool schemas for runtime discovery and model invocation.
How it connects
Connects MCP tool discovery with function calling and the OpenAI runtime.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Building Reliable AI Systems. The section links point to the parts of the book it draws on.