Agno supports using MongoDB as a storage backend for Teams using the MongoDb class.

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Usage

You need to provide either db_url or client. The following example uses db_url.

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Run MongoDB

Install docker desktop and run MongoDB on port 27017 using: 
docker run -d \
  --name local-mongo \
  -p 27017:27017 \
  -e MONGO_INITDB_ROOT_USERNAME=mongoadmin \
  -e MONGO_INITDB_ROOT_PASSWORD=secret \
  mongo
mongodb_for_team.py
"""
Run: `pip install openai ddgs newspaper4k lxml_html_clean agno` to install the dependencies
"""
from typing import List

from agno.agent import Agent
from agno.db.mongo import MongoDb
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.hackernews import HackerNewsTools
from pydantic import BaseModel

# MongoDB connection settings
db_url = "mongodb://localhost:27017"
db = MongoDb(db_url=db_url)


class Article(BaseModel):
    title: str
    summary: str
    reference_links: List[str]


hn_researcher = Agent(
    name="HackerNews Researcher",
    model=OpenAIChat("gpt-5-mini"),
    role="Gets top stories from hackernews.",
    tools=[HackerNewsTools()],
)

web_searcher = Agent(
    name="Web Searcher",
    model=OpenAIChat("gpt-5-mini"),
    role="Searches the web for information on a topic",
    tools=[DuckDuckGoTools()],
    add_datetime_to_context=True,
)


hn_team = Team(
    name="HackerNews Team",
    model=OpenAIChat("gpt-5-mini"),
    members=[hn_researcher, web_searcher],
    db=db,
    instructions=[
        "First, search hackernews for what the user is asking about.",
        "Then, ask the web searcher to search for each story to get more information.",
        "Finally, provide a thoughtful and engaging summary.",
    ],
    output_schema=Article,
    markdown=True,
    debug_mode=True,
    show_members_responses=True,
    add_member_tools_to_context=False,
)

hn_team.print_response("Write an article about the top 2 stories on hackernews")

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Params

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Developer Resources