See, plan and edit your AI agents.

billing = Agent(
    "openai:gpt-5-mini",
    name="billing",
    toolsets=[crm.prefixed("crm")],
)

tech = Agent(
    "anthropic:claude-sonnet-5-5",
    name="tech",
    tools=[Tool(status_page, takes_ctx=False)],
    toolsets=[help_center],  # MCPToolset
    capabilities=[
        NativeTool(WebSearchTool()),
        Thinking(effort="medium"),
    ],
)

triage = Agent("openai:gpt-5", name="triage")

@triage.tool
async def ask_billing(ctx, question: str) -> str:
    # an agent run inside a tool: delegation
    r = await billing.run(question, deps=ctx.deps)
    return r.output

@tool
def plot(path: str, x: str, y: str) -> str:
    """Draw a line chart and return the image path."""

web_researcher = ToolCallingAgent(
    tools=[WebSearchTool(), VisitWebpageTool()],
    model=model,
    name="web_researcher",
    description="Searches the web, reads pages.",
)

analyst = CodeAgent(
    tools=[CsvSummary(), plot],
    model=model,
    name="analyst",
    description="Analyses CSV data.",
)

papers = StdioServerParameters(command="uvx", ...)

with ToolCollection.from_mcp(papers, ...) as arxiv:
    lead = CodeAgent(
        tools=[*arxiv.tools],
        model=model,
        managed_agents=[web_researcher, analyst],
    )

# written by agentsdiagram edit / the diagram
@tool
def search_flights(origin: str, destination: str,
                   date: str) -> list[dict]:
    """Flights between two cities on a date.

    Args: ...
    """
    raise NotImplementedError("agentsdiagram: planned")

maps_mcp = MCPClient({"url": "https://maps.example.com/mcp", ...})

# agentsdiagram: planned
booker = ToolCallingAgent(
    tools=[search_flights, *maps_mcp.get_tools()],
    model=model,
    name="booker",
    description="Finds and books flights and hotels.",
)

assistant = CodeAgent(
    tools=[get_weather, WebSearchTool()],
    model=model,
    managed_agents=[booker],  # added
)

One file: a manager CodeAgent with two managed agents and MCP tools. Full source