Gemini Interactions - Deep Research with MCP servers

Give the Deep Research agent access to external tools via remote MCP servers.

Give the Deep Research agent access to external tools via remote MCP servers. Pass server configs through mcp_servers; type: "mcp_server" is added automatically. Only url is strictly required; name, headers, and allowed_tools are optional.

This example uses the placeholder MCP host mcp.example.com and the placeholder bearer token my-token. It cannot contact a real MCP server unchanged.

deep_research_mcp.py

"""
Gemini Interactions - Deep Research with MCP servers
=====================================================

Give the Deep Research agent access to external tools via remote MCP servers.
Pass server configs through `mcp_servers`; `type: "mcp_server"` is added
automatically. Only `url` is strictly required; `name`, `headers`, and
`allowed_tools` are optional.

Custom Function Calling tools are NOT supported by Deep Research, but remote
MCP servers are.
"""

from agno.agent import Agent
from agno.models.google import GeminiInteractions

agent = Agent(
    model=GeminiInteractions(
        agent="deep-research-preview-04-2026",
        thinking_summaries="auto",
        mcp_servers=[
            {
                "name": "Deployment Tracker",
                "url": "https://mcp.example.com/mcp",
                "headers": {"Authorization": "Bearer my-token"},
                # "allowed_tools": ["get_status"],  # optionally restrict
            }
        ],
    ),
    markdown=True,
)

if __name__ == "__main__":
    agent.print_response(
        "Check the status of my last server deployment and summarize any issues."
    )

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 google-genai
   
3. Export your Google API key

   Mac/Linux

   export GOOGLE_API_KEY="your_google_api_key_here"
   

   $Env:GOOGLE_API_KEY="your_google_api_key_here"
   
4. Configure the MCP server

   Replace https://mcp.example.com/mcp with your remote MCP endpoint and replace Bearer my-token with the credential that server expects. Remove the headers entry if the server does not require it.

5. Run the example

   Save the code above as deep_research_mcp.py, then run:

   python deep_research_mcp.py
   

Full source: cookbook/90_models/google/gemini_interactions/deep_research_mcp.py