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

# GCS for Team

Agno supports using Google Cloud Storage (GCS) as a storage backend for Teams using the `GcsJsonDb` class. This storage backend stores session data as JSON blobs in a GCS bucket.

## Usage

Configure your team with GCS storage to enable cloud-based session persistence.

```python gcs_for_team.py theme={null}
"""
Run: `uv pip install openai newspaper4k lxml_html_clean agno` to install the dependencies
"""

import uuid
import google.auth
from typing import List

from agno.agent import Agent
from agno.db.gcs_json import GcsJsonDb
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.hackernews import HackerNewsTools
from pydantic import BaseModel

# Obtain the default credentials and project id from your gcloud CLI session.
credentials, project_id = google.auth.default()

# Generate a unique bucket name using a base name and a UUID4 suffix.
base_bucket_name = "example-gcs-bucket"
unique_bucket_name = f"{base_bucket_name}-{uuid.uuid4().hex[:12]}"
print(f"Using bucket: {unique_bucket_name}")

# Setup the JSON database
db = GcsJsonDb(
    bucket_name=unique_bucket_name,
    prefix="team/",
    project=project_id,
    credentials=credentials,
)

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

hn_researcher = Agent(
    name="HackerNews Researcher",
    model=OpenAIResponses(id="gpt-5.2"),
    role="Gets top stories from hackernews.",
    tools=[HackerNewsTools()],
)

web_searcher = Agent(
    name="Web Searcher",
    model=OpenAIResponses(id="gpt-5.2"),
    role="Searches the web for information on a topic",
    tools=[HackerNewsTools()],
    add_datetime_to_context=True,
)

hn_team = Team(
    name="HackerNews Team",
    model=OpenAIResponses(id="gpt-5.2"),
    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,
)

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

## Prerequisites

<Snippet file="gcs-auth-storage.mdx" />

## Params

<Snippet file="db-gcs-params.mdx" />