Async MongoDB for Agent - Agno

Agno supports using MongoDB asynchronously as a storage backend for Agents, with the AsyncMongoDb class.

Usage

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

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

async_mongodb_for_agent.py

"""
Run `uv pip install agno openai motor pymongo` to install dependencies.
"""
from agno.agent import Agent
from agno.db.mongo import AsyncMongoDb
from agno.tools.hackernews import HackerNewsTools

# MongoDB connection settings
db_url = "mongodb://localhost:27017"

db = AsyncMongoDb(db_url=db_url)

agent = Agent(
    db=db,
    tools=[HackerNewsTools()],
    add_history_to_context=True,
)
agent.print_response("How many people live in Canada?")
agent.print_response("What is their national anthem called?")

Params

Parameter	Type	Default	Description
`id`	`Optional[str]`	-	The ID of the database instance. UUID by default.
`db_client`	`Optional[MongoClient]`	-	The MongoDB client to use.
`db_name`	`Optional[str]`	-	The name of the database to use.
`db_url`	`Optional[str]`	-	The database URL to connect to.
`session_collection`	`Optional[str]`	-	Name of the collection to store sessions.
`memory_collection`	`Optional[str]`	-	Name of the collection to store memories.
`metrics_collection`	`Optional[str]`	-	Name of the collection to store metrics.
`eval_collection`	`Optional[str]`	-	Name of the collection to store evaluation runs.
`knowledge_collection`	`Optional[str]`	-	Name of the collection to store knowledge documents.
`traces_collection`	`Optional[str]`	-	Name of the collection to store traces.
`spans_collection`	`Optional[str]`	-	Name of the collection to store spans.