Converts inputs into a persistent, searchable graph-based memory for AI agents via asynchronous Python API.
npx skills add https://github.com/topoteretes/cognee --skill cognee
Please help me install this Agent Skill. Skill: cognee Source: https://github.com/topoteretes/cognee/tree/main/cognee Command: npx skills add https://github.com/topoteretes/cognee --skill cognee
Cognee provides a knowledge engine that creates persistent, cross-session memory for AI agents by turning inputs into graph-based memory and enabling retrieval across sessions.
Ingest data with add, transform it into a knowledge graph with cognify, and query insights with search.
High-intent search queries and answers about installing and using this skill.
Persistent memory for AI agents is created by converting inputs into a searchable knowledge graph using cognify, enabling cross-session retrieval across tasks and agents. You ingest data with add, transform it, and query insights with search.
Knowledge graph memory management transforms ingested text, files, and URLs into a structured graph, enabling multi-user memory scoping and searchable retrieval. This mechanism supports feedback loops, memory enrichment, and self-improving agent workflows.
You scope AI agent memory by managing datasets and NodeSets to isolate context for tenants, teams, or individual agents. This ensures cross-session retrieval remains specific to the designated context and prevents data overlap between users.
Yes, you can build and query a persistent knowledge graph using an asynchronous Python API. It exposes add, cognify, search, memify, datasets, prune, and visualize functions, requiring integration with storage paths, graph, and vector DB backends.
The best way to maintain a knowledge graph is using the visualize function to inspect graph structure and the prune function to remove stale data. This supports self-improving workflows via memory enrichment and visualizations.
Yes, you need to integrate storage paths, graph DB backends, and vector DB backends to build persistent AI agent memory. These backends store the graph structure and enable the various search types required for cross-session retrieval.
aresbitCreate, read, and update Notion pages, databases, and blocks via the Notion API.
drt0927Aggregate team learnings into a searchable append-only log with export.
mem0aiStore, retrieve, and manage user memories across AI applications.
bmsull560Integrate vector-based memory with knowledge graphs for multi-session conversation context.
