cognee-mcp

import asyncio import cognee import os from pprint import pprint # By default cognee uses OpenAI's gpt-5-mini LLM model # Provide your OpenAI LLM API KEY os.environ["LLM_API_KEY"] = "" async def cognee_demo(): # Get file path to document to process from pathlib import Path current_directory = Path(__file__).resolve().parent.parent file_path = os.path.join(current_directory, "data", "alice_in_wonderland.txt") await cognee.prune.prune_data() await cognee.prune.prune_system(metadata=True) # Call Cognee to process document await cognee.add(file_path) await cognee.cognify() # Query Cognee for information from provided document answer = await cognee.search("List me all the important characters in Alice in Wonderland.") pprint(answer) answer = await cognee.search("How did Alice end up in Wonderland?") pprint(answer) answer = await cognee.search("Tell me about Alice's personality.") pprint(answer) # Cognee is an async library, it has to be called in an async context asyncio.run(cognee_demo())