# Agent visualization

Agent visualization allows you to generate a structured graphical representation of agents and their relationships using **Graphviz**. This is useful for understanding how agents, tools, and handoffs interact within an application.

## Installation

Install the optional `viz` dependency group:

```bash
pip install "openai-agents[viz]"
```

## Generating a graph

You can generate an agent visualization using the `draw_graph` function. This function creates a directed graph where:

- **Agents** are represented as yellow boxes.
- **MCP servers** are represented as grey boxes.
- **Tools** are represented as green ellipses.
- **Handoffs** are directed edges from one agent to another.

### Example usage

```python
import os

from agents import Agent, function_tool
from agents.mcp.server import MCPServerStdio
from agents.extensions.visualization import draw_graph

@function_tool
def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny."

spanish_agent = Agent(
    name="Spanish agent",
    instructions="You only speak Spanish.",
)

english_agent = Agent(
    name="English agent",
    instructions="You only speak English",
)

current_dir = os.path.dirname(os.path.abspath(__file__))
samples_dir = os.path.join(current_dir, "sample_files")
mcp_server = MCPServerStdio(
    name="Filesystem Server, via npx",
    params={
        "command": "npx",
        "args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
    },
)

triage_agent = Agent(
    name="Triage agent",
    instructions="Handoff to the appropriate agent based on the language of the request.",
    handoffs=[spanish_agent, english_agent],
    tools=[get_weather],
    mcp_servers=[mcp_server],
)

draw_graph(triage_agent)
```

![Agent Graph](./assets/images/graph.png)

This generates a graph that visually represents the structure of the **triage agent** and its connections to sub-agents and tools.


## Understanding the visualization

The generated graph includes:

- A **start node** (`__start__`) indicating the entry point.
- Agents represented as **rectangles** with yellow fill.
- Tools represented as **ellipses** with green fill.
- MCP servers represented as **rectangles** with grey fill.
- Directed edges indicating interactions:
  - **Solid arrows** for agent-to-agent handoffs.
  - **Dotted arrows** for tool invocations.
  - **Dashed arrows** for MCP server invocations.
- An **end node** (`__end__`) indicating where execution terminates.

**Note:** MCP servers are rendered in recent versions of the `agents` package (verified in **v0.2.8**). If you don’t see MCP boxes in your visualization, upgrade to the latest release.

## Customizing the graph

### Showing the graph
By default, `draw_graph` displays the graph inline. To show the graph in a separate window, write the following:

```python
draw_graph(triage_agent).view()
```

### Saving the graph
By default, `draw_graph` displays the graph inline. To save it as a file, specify a filename:

```python
draw_graph(triage_agent, filename="agent_graph")
```

This will generate `agent_graph.png` in the working directory.
