Test Client

MCP client example: an agent that operates an AgentOS through its MCP server.

test_client.py

"""
MCP client example: an agent that operates an AgentOS through its MCP server.

First run the AgentOS with the MCP server enabled:

```bash
.venvs/demo/bin/python cookbook/05_agent_os/mcp_demo/mcp_server_example.py
```

Then run this client in a second terminal. It connects to the AgentOS MCP server
at /mcp and drives it through the 8 built-in tools: discover the OS
(get_agentos_config), run components (run_agent / run_team / run_workflow),
resolve pauses (continue_run), stop runs (cancel_run), and browse conversations
(get_sessions / get_session_runs).
"""

import asyncio
from uuid import uuid4

from agno.agent import Agent
from agno.db.in_memory import InMemoryDb
from agno.models.openai import OpenAIResponses
from agno.tools.mcp import MCPTools

# ---------------------------------------------------------------------------
# Create Example
# ---------------------------------------------------------------------------

# This is the URL of the MCP server we want to use.
server_url = "http://localhost:7777/mcp"

session_id = f"session_{uuid4()}"


async def run_agent() -> None:
    async with MCPTools(
        transport="streamable-http", url=server_url, timeout_seconds=60
    ) as mcp_tools:
        agent = Agent(
            model=OpenAIResponses(id="gpt-5.5"),
            tools=[mcp_tools],
            instructions=[
                "You operate an AgentOS through its MCP tools.",
                "Call get_agentos_config first to discover the agents, teams, and workflows you can run.",
                "Use the run tools to delegate work, and the session tools to review past conversations.",
            ],
            user_id="[e-mail]",
            session_id=session_id,
            db=InMemoryDb(),
            add_session_state_to_context=True,
            add_history_to_context=True,
            markdown=True,
        )

        await agent.aprint_response(
            input="Which agents do I have in my AgentOS?", stream=True, markdown=True
        )

        # await agent.aprint_response(
        #     input="Use my web research agent to find the latest news about AI",
        #     stream=True,
        #     markdown=True,
        # )

        ## Session history
        # await agent.aprint_response(
        #     input="List my recent sessions and summarize what the last conversation was about.",
        #     stream=True,
        #     markdown=True,
        # )


# ---------------------------------------------------------------------------
# Run Example
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    asyncio.run(run_agent())

Run the Example

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U "agno[mcp,os]" anthropic ddgs openai
   
3. Export your API keys

   Mac/Linux

   export ANTHROPIC_API_KEY="your_anthropic_api_key_here"
   export OPENAI_API_KEY="your_openai_api_key_here"
   

   $Env:ANTHROPIC_API_KEY="your_anthropic_api_key_here"
   $Env:OPENAI_API_KEY="your_openai_api_key_here"
   
4. Clone Agno

   Clone the repository and run the remaining commands from its root:

   git clone https://github.com/agno-agi/agno.git
   cd agno
   
5. Start the AgentOS MCP server

   In another terminal, start the server on port 7777:

   python cookbook/05_agent_os/mcp_demo/mcp_server_example.py
   
6. Run the example

   Run the example from the repository root:

   python cookbook/05_agent_os/mcp_demo/test_client.py
   

Full source: cookbook/05_agent_os/mcp_demo/test_client.py