Agents and Tools
Workflow steps can call agents to leverage LLM reasoning or call tools for type-safe logic. You can either invoke them from within a step’s execute
function or compose them directly as steps using createStep()
.
Using agents in workflows
Use agents in workflow steps when you need reasoning, language generation, or other LLM-based tasks. Call from a step’s execute
function for more control over the agent call (e.g., track conversation history or return structured output). Compose agents as steps when you don’t need to modify how the agent is invoked.
Calling agents
Call agents inside a step’s execute
function using .generate()
or .stream()
. This lets you modify the agent call and handle the response before passing it to the next step.
const step1 = createStep({
// ...
execute: async ({ inputData, mastra }) => {
const { message } = inputData;
const testAgent = mastra.getAgent("testAgent");
const response = await testAgent.generate(`Convert this message into bullet points: ${message}`, {
memory: {
thread: "user-123",
resource: "test-123"
}
});
return {
list: response.text
};
}
});
See Calling Agents for more examples.
Agents as steps
Compose an agent as a step using createStep()
when you don’t need to modify the agent call. Use .map()
to transform the previous step’s output into a prompt
the agent can use.
import { testAgent } from "../agents/test-agent";
const step1 = createStep(testAgent);
export const testWorkflow = createWorkflow({
// ...
})
.map(async ({ inputData }) => {
const { message } = inputData;
return {
prompt: `Convert this message into bullet points: ${message}`
};
})
.then(step1)
.then(step2)
.commit();
See Input Data Mapping for more information.
Using tools in workflows
Use tools in workflow steps to leverage existing tool logic. Call from a step’s execute
function when you need to prepare context or process responses. Compose tools as steps when you don’t need to modify how the tool is used.
Calling tools
Call tools inside a step’s execute
function using .execute()
. This gives you more control over the tool’s input context, or process its response before passing it to the next step.
import { testTool } from "../tools/test-tool";
const step2 = createStep({
// ...
execute: async ({ inputData, runtimeContext }) => {
const { formatted } = inputData;
const response = await testTool.execute({
context: {
text: formatted
},
runtimeContext
});
return {
emphasized: response.emphasized
};
}
});
See Calling Tools for more examples.
Tools as steps
Compose a tool as a step using createStep()
when the previous step’s output matches the tool’s input context. You can use .map()
to transform the previous step’s output if they don’t.
import { testTool } from "../tools/test-tool";
const step2 = createStep(testTool);
export const testWorkflow = createWorkflow({
// ...
})
.then(step1)
.map(async ({ inputData }) => {
const { formatted } = inputData;
return {
text: formatted
};
})
.then(step2)
.commit();
See Input Data Mapping for more information.