mcp-use__mcp-use/docs/python/agent/structured-output.mdx

---
title: "Agent Structured Output"
description: "Get strongly-typed Pydantic models with intelligent retry logic"
icon: "shapes"
---

The MCPAgent supports structured output, allowing you to get strongly-typed Pydantic models instead of plain text responses. The agent becomes **schema-aware** and will intelligently retry to gather missing information until all required fields can be populated.

## How it Works

When you provide an `output_schema` parameter, the agent:

1. **Understands requirements** - The agent knows exactly what information it needs to collect
2. **Attempts structured output** - At completion points, tries to format the result into your schema
3. **Intelligently retries** - If required fields are missing, continues execution to gather the missing data
4. **Validates completeness** - Only finishes when all required fields can be populated

## Basic Example

<CodeGroup>
```python Python
import asyncio
from pydantic import BaseModel, Field
from langchain_openai import ChatOpenAI
from mcp_use import MCPAgent, MCPClient

class WeatherInfo(BaseModel):
    """Weather information for a location"""
    city: str = Field(description="City name")
    temperature: float = Field(description="Temperature in Celsius")
    condition: str = Field(description="Weather condition")
    humidity: int = Field(description="Humidity percentage")

async def main():
    # Setup client and agent
    client = MCPClient(config={"mcpServers": {...}})
    llm = ChatOpenAI(model="gpt-5.5")
    agent = MCPAgent(llm=llm, client=client)

    # Get structured output
    weather: WeatherInfo = await agent.run(
        "Get the current weather in San Francisco",
        output_schema=WeatherInfo
    )

    print(f"Temperature in {weather.city}: {weather.temperature}°C")
    print(f"Condition: {weather.condition}")
    print(f"Humidity: {weather.humidity}%")

asyncio.run(main())
```
</CodeGroup>

## Key Benefits

- **Type Safety**: Get Pydantic (Python) or Zod (TypeScript) models with full IDE support and validation
- **Intelligent Gathering**: Agent knows what information is required and won't stop until it has everything
- **Automatic Retry**: Missing fields trigger continued execution automatically
- **Field Validation**: Built-in validation for required fields, data types, and constraints

The agent will continue working until all required fields in your schema can be populated, ensuring you always get complete, structured data.