# Postgres for Team (/database/providers/postgres/usage/postgres-for-team) `PostgresDb` stores a Team's sessions and run history in PostgreSQL. ## Usage [#usage] Start in a [virtual environment](/sdk/setup). Install dependencies: ```shell uv pip install agno openai ddgs sqlalchemy "psycopg[binary]" ``` Export your OpenAI API key: ```shell export OPENAI_API_KEY="your_openai_api_key_here" ``` ### Run PostgreSQL [#run-postgresql] Install [Docker Desktop](https://docs.docker.com/get-started/get-docker/), then start PostgreSQL with pgvector on port `5532`: ```bash docker run -d \ -e POSTGRES_DB=ai \ -e POSTGRES_USER=ai \ -e POSTGRES_PASSWORD=ai \ -e PGDATA=/var/lib/postgresql \ -v pgvolume:/var/lib/postgresql \ -p 5532:5432 \ --name pgvector \ agnohq/pgvector:18 ``` ```python title="postgres_for_team.py" from typing import List from agno.agent import Agent from agno.db.postgres import PostgresDb from agno.models.openai import OpenAIResponses from agno.team import Team from agno.tools.hackernews import HackerNewsTools from agno.tools.websearch import WebSearchTools from pydantic import BaseModel db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai" db = PostgresDb(db_url=db_url) 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=[WebSearchTools()], 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, summarize each story and include its reference links.", ], output_schema=Article, markdown=True, show_members_responses=True, ) hn_team.print_response("Write an article about the top 2 stories on HackerNews") ``` ## Run the example [#run-the-example] Save the code as `postgres_for_team.py`, start the database described above, and run: ```shell python postgres_for_team.py ``` ## Parameters [#parameters] | Parameter | Type | Default | Description | | -------------------------------- | ------------------ | ------- | ---------------------------------------------------------------------------------------------------------------- | | `id` | `Optional[str]` | - | The ID of the database instance. UUID by default. | | `db_url` | `Optional[str]` | - | The database URL to connect to. | | `db_engine` | `Optional[Engine]` | - | The SQLAlchemy database engine to use. | | `db_schema` | `Optional[str]` | - | The database schema to use. | | `session_table` | `Optional[str]` | - | Name of the table to store Agent, Team and Workflow sessions. | | `runs_table` | `Optional[str]` | - | Name of the table to store the runs of each session. | | `memory_table` | `Optional[str]` | - | Name of the table to store memories. | | `metrics_table` | `Optional[str]` | - | Name of the table to store metrics. | | `eval_table` | `Optional[str]` | - | Name of the table to store evaluation runs data. | | `knowledge_table` | `Optional[str]` | - | Name of the table to store knowledge content. | | `traces_table` | `Optional[str]` | - | Name of the table to store traces. | | `spans_table` | `Optional[str]` | - | Name of the table to store spans. | | `versions_table` | `Optional[str]` | - | Name of the table to store schema versions. | | `components_table` | `Optional[str]` | - | Name of the table to store components. | | `component_configs_table` | `Optional[str]` | - | Name of the table to store component configurations. | | `component_links_table` | `Optional[str]` | - | Name of the table to store links between components. | | `learnings_table` | `Optional[str]` | - | Name of the table to store learnings. | | `schedules_table` | `Optional[str]` | - | Name of the table to store cron schedules. | | `schedule_runs_table` | `Optional[str]` | - | Name of the table to store schedule run history. | | `job_table` | `Optional[str]` | - | Name of the table to store durable background run jobs. | | `approvals_table` | `Optional[str]` | - | Name of the table to store human approval requests. | | `auth_tokens_table` | `Optional[str]` | - | Name of the table to store OAuth tokens for external services. | | `service_accounts_table` | `Optional[str]` | - | Name of the table to store service accounts. | | `mcp_oauth_clients_table` | `Optional[str]` | - | Name of the table to store MCP OAuth client registrations. | | `mcp_oauth_transactions_table` | `Optional[str]` | - | Name of the table to store MCP OAuth transactions. | | `mcp_oauth_codes_table` | `Optional[str]` | - | Name of the table to store MCP OAuth authorization codes. | | `mcp_oauth_refresh_tokens_table` | `Optional[str]` | - | Name of the table to store MCP OAuth refresh tokens. | | `mcp_oauth_keys_table` | `Optional[str]` | - | Name of the table to store MCP OAuth signing keys. | | `create_schema` | `bool` | `True` | Whether to create the database schema if it doesn't exist. Set to `False` when the schema is managed externally. |