MySQL Workflow Storage

Agno supports using MySQL as a storage backend for Workflows using the MysqlDb class.

Usage

Run MySQL

Install docker desktop and run MySQL on port 3306 using:

docker run -d \
  --name mysql \
  -e MYSQL_ROOT_PASSWORD=ai \
  -e MYSQL_DATABASE=ai \
  -e MYSQL_USER=ai \
  -e MYSQL_PASSWORD=ai \
  -p 3306:3306 \
  -d mysql:8

mysql_for_workflow.py

from agno.agent import Agent
from agno.db.mysql import MySQLDb
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.hackernews import HackerNewsTools
from agno.workflow.step import Step
from agno.workflow.workflow import Workflow

db_url = "mysql+pymysql://ai:ai@localhost:3306/ai"

db = MySQLDb(db_url=db_url)

# Define agents
hackernews_agent = Agent(
    name="Hackernews Agent",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[HackerNewsTools()],
    role="Extract key insights and content from Hackernews posts",
)
web_agent = Agent(
    name="Web Agent",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[HackerNewsTools()],
    role="Search the web for the latest news and trends",
)

# Define research team for complex analysis
research_team = Team(
    name="Research Team",
    members=[hackernews_agent, web_agent],
    instructions="Research tech topics from Hackernews and the web",
)

content_planner = Agent(
    name="Content Planner",
    model=OpenAIResponses(id="gpt-5.2"),
    instructions=[
        "Plan a content schedule over 4 weeks for the provided topic and research content",
        "Ensure that I have posts for 3 posts per week",
    ],
)

# Define steps
research_step = Step(
    name="Research Step",
    team=research_team,
)

content_planning_step = Step(
    name="Content Planning Step",
    agent=content_planner,
)

# Create and use workflow
if __name__ == "__main__":
    content_creation_workflow = Workflow(
        name="Content Creation Workflow",
        description="Automated content creation from blog posts to social media",
        db=db,
        steps=[research_step, content_planning_step],
    )
    content_creation_workflow.print_response(
        input="AI trends in 2024",
        markdown=True,
    )

Params

Parameter	Type	Default	Description
id	Optional[str]	-	The ID of the database instance. UUID by default.
db_engine	Optional[Engine]	-	The SQLAlchemy database engine to use.
db_schema	Optional[str]	-	The database schema to use.
db_url	Optional[str]	-	The database URL to connect to.
session_table	Optional[str]	-	Name of the table to store Agent, Team and Workflow sessions.
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.