> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# MongoDB for Team

> HackerNews research team stores its sessions in MongoDB with a structured Article output.

````python mongodb_for_team.py theme={null}
"""
Use MongoDb as the database for a team.

Run `uv pip install openai ddgs newspaper4k lxml_html_clean agno` to install the dependencies

Run a local MongoDB server using:
```bash
docker run -d \
  --name local-mongo \
  -p 27017:27017 \
  -e MONGO_INITDB_ROOT_USERNAME=mongoadmin \
  -e MONGO_INITDB_ROOT_PASSWORD=secret \
  mongo
```
or use our script:
```bash
./cookbook/scripts/run_mongodb.sh
"""

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.hackernews import HackerNewsTools
from agno.tools.websearch import WebSearchTools
from pydantic import BaseModel

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
db_url = "mongodb://mongoadmin:secret@localhost:27017"
db = MongoDb(db_url=db_url)


# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
class Article(BaseModel):
    title: str
    summary: str
    reference_links: List[str]


hn_researcher = Agent(
    name="HackerNews Researcher",
    model=OpenAIChat("gpt-5.6-luna"),
    role="Gets top stories from hackernews.",
    tools=[HackerNewsTools()],
)

web_searcher = Agent(
    name="Web Searcher",
    model=OpenAIChat("gpt-5.6-luna"),
    role="Searches the web for information on a topic",
    tools=[WebSearchTools()],
    add_datetime_to_context=True,
)


hn_team = Team(
    name="HackerNews Team",
    model=OpenAIChat("gpt-5.6-luna"),
    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,
    show_members_responses=True,
    add_member_tools_to_context=False,
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    hn_team.print_response("Write an article about the top 2 stories on hackernews")
````

## Run the Example

<Snippet file="create-venv-step.mdx" />

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno ddgs openai pymongo
```

**2. Export your OpenAI API key**

```bash Mac/Linux theme={null}
export OPENAI_API_KEY="your_openai_api_key_here"
```

```bash Windows theme={null}
$Env:OPENAI_API_KEY="your_openai_api_key_here"
```

**3. Run MongoDB**

```bash theme={null}
docker run -d -p 27017:27017 --name mongodb mongo:latest
```

**4. Run the example**

Save the code above as `mongodb_for_team.py`, then run:

```bash theme={null}
python mongodb_for_team.py
```

Full source: [cookbook/06\_storage/mongo/mongodb\_for\_team.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/06_storage/mongo/mongodb_for_team.py)


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.