custom_tools.py
"""
Expose one custom MCP tool
==========================
Replace the eight built-in AgentOS MCP tools with one purpose-built tool. The
tool routes a question through an agent while AgentOS owns the MCP transport,
mount, and lifespan.
Prerequisites: OPENAI_API_KEY
Run: .venvs/demo/bin/python cookbook/05_agent_os/14_mcp/custom_tools.py
Try: connect an MCP client to http://localhost:7777/mcp and call ask_workspace
"""
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS, MCPConfig
from agno.tools import tool
# ---------------------------------------------------------------------------
# Create the custom tool
# ---------------------------------------------------------------------------
db = SqliteDb(
id="mcp-custom-tools-db",
db_file="tmp/mcp_custom_tools.db",
)
workspace_agent = Agent(
id="workspace-agent",
name="Workspace Agent",
model=OpenAIResponses(id="gpt-5.5"),
db=db,
instructions="Answer workspace questions clearly and concisely.",
)
@tool(
name="ask_workspace",
title="Ask the Workspace Agent",
description="Ask the workspace agent a question",
# A custom tool publishes whatever it declares here and nothing more, so state all
# three hints: a client that finds one missing falls back to a protocol default,
# and a directory submission is rejected outright for leaving any of them unset.
# These are true of this tool: the run persists a session (not read-only), it only
# appends (nothing destroyed), and the agent calls a model over the network.
annotations={
"readOnlyHint": False,
"destructiveHint": False,
"openWorldHint": True,
},
)
async def ask_workspace(question: str) -> str:
"""Route one question through the workspace agent."""
response = await workspace_agent.arun(question)
return response.content or ""
# ---------------------------------------------------------------------------
# Serve only the custom tool
# ---------------------------------------------------------------------------
agent_os = AgentOS(
id="mcp-custom-tools-os",
description="AgentOS exposing one purpose-built MCP tool.",
db=db,
agents=[workspace_agent],
mcp=MCPConfig(
tools=[ask_workspace],
default_tools=False,
),
)
app = agent_os.get_app()
# ---------------------------------------------------------------------------
# Run Custom Tool AgentOS
# ---------------------------------------------------------------------------
if __name__ == "__main__":
agent_os.serve(app=app)
Run the Example
1
Set up your virtual environment
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]" openai
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
custom_tools.py, then run:python custom_tools.py