Programming

Connecting Notion to Cognee: Building Long-Term Memory for AI Agents

AI agents often lose context across sessions. By integrating Notion with Cognee, agents can automatically ingest workspace documentation and convert it into an interconnected Knowledge Graph. How it works I developed NotionLoader using the official notion-client Python SDK. It fetches pages and databases, extracts text content, and passes it to Cognee's ingestion pipeline. Python from notion_loader import NotionLoader import cognee loader = NotionLoader() pages = loader.load_data() for page in p

AI agents often lose context across sessions. By integrating Notion with Cognee, agents can automatically ingest workspace documentation and convert it into an interconnected Knowledge Graph.

How it works
I developed NotionLoader using the official notion-client Python SDK. It fetches pages and databases, extracts text content, and passes it to Cognee's ingestion pipeline.

Python
from notion_loader import NotionLoader
import cognee

loader = NotionLoader()
pages = loader.load_data()

for page in pages:
cognee.add(f"Title: {page['title']}\n\n{page['content']}")

cognee.cognify()
This brings seamless knowledge graph memory to any Cognee agent working with Notion documents!