Tool

A Tool is a catalog resource that describes a discrete, executable capability that an Agent can invoke during a conversation. Tools are how agents extend their abilities beyond pure language generation: they can search the web, read a web page, run code, query systems, or interact with any external service exposed through an MCP server.

A tool has one of two sources:

• Built-in tools are implemented inside the AI Foundry runtime and belong to an App.
• MCP Server tools are exposed by a registered MCP Server. You rarely create them by hand: from the MCP server's detail page, Discover Tools lists the tools the server exposes and adds the ones you select to the Catalog.

Tool reference

Besides the common metadata (Title, Name, Description, and optional Tags), a tool has the spec fields below. The Name is auto-derived from the title, can contain lowercase letters, digits, dots, and hyphens (starting and ending with a letter or digit, up to 63 characters), and is immutable after creation. Agents reference it in spec.tools.

Field	Type	Required	Description
type	string	Yes	The tool source: built-in or mcp-server. The form shows an additional field depending on the selected type.
application.name	string	Conditional	Required when type is built-in. The App this tool belongs to, selected in the Application field.
mcpServer.name	string	Conditional	Required when type is mcp-server. The MCP server that exposes this tool, selected in the MCP Server Name field.
runtimeName	string	Yes	The identifier the runtime uses to invoke the tool, for example web_search. It must start with a letter, followed by letters, digits, underscores, or hyphens. For MCP tools it is the tool name as exposed by the server.
category	string	No	A grouping label. Tools with the same category are shown together in the agent's tool picker.
enabled	boolean	No	When false, the tool is skipped when the agent is built, so it is unavailable at runtime. Defaults to true.

In the Tools list you can filter by type, application, and MCP server.

Writing good tool descriptions

The tool's description helps the LLM decide when to call it. A clear, accurate description directly improves agent behavior:

• State what the tool does in the first sentence: "Searches the internal knowledge base for articles matching a query."
• Describe the input format: "Input: a natural-language question string."
• Describe the output format: "Output: up to five article snippets with titles and URLs."
• Note limitations: "Only covers articles published after 2023-01-01."

Avoid vague names or descriptions: the LLM uses them to reason about when a tool is appropriate.

Attaching tools to agents

In the agent form, the tool picker lists every registered tool in two sections, Applications' Tools and MCP Server's Tools, grouped by App or MCP server and then by category. You can select tools one by one or a whole group at once.

In the AI Playground you can enable or disable individual tools for a live session without modifying the agent. This is useful for debugging unexpected tool calls.

Tools added by the platform

Some tools are not catalog items: the runtime attaches them to an agent depending on how it is configured.

• Memory tools: when Memory is enabled for the installation, every agent gets load_memory, list_memories, and remember, unless its configuration opts it out.
• Workspace tools: an agent that runs inside an Agentic Workflow can work in the run's shared workspace. workspaceTools grants the tools that list and read files, workspaceWrites adds the tools that write and edit files, and workspaceCommands adds a tool that runs commands. Each setting includes the ones before it, and all of them require a workspace service to be configured.

Tools vs. skills

Both tools and skills extend what an agent can do, but they operate at different levels of abstraction:

Aspect	Tool	Skill
Granularity	Fine-grained, single operation	Higher-level, multi-step capability
Implementation	AI Foundry runtime or MCP server	Instructions, references, and scripts stored in a Skill
Attached to	Agents	Agents and playbooks
Invoked by	The model, through function calling	The model, which loads the skill when a request matches it

See also

• Agent: attaches tools in spec.tools.
• MCP Server: a server that exposes tools through the Model Context Protocol.
• App: the application or plugin that a built-in tool belongs to.
• Skill: higher-level reusable capabilities.
• Guardrail: policies that can run before or during an MCP tool call.