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Cognee
Open-source graph memory platform that turns documents and chats into a permissioned knowledge graph for AI agents to recall with citations and context.
$5Starting price
160KMonthly visits
37Popularity
About Cognee
Cognee is an open-source memory platform that converts documents, chats, and data sources into a graph memory agents can recall across sessions. It integrates via MCP and SDKs, adds citations and governance, and scales from local installs to managed Cognee Cloud. Installation is straightforward: run pip install cognee, execute the quickstart, and connect an initial data source. Agents read and write through MCP or SDK calls, retrieving cited snippets and structured facts while permissions, workspaces, and schemas control who sees what. The platform supports custom ontologies and schemas to model domains precisely, aligning memory with business rules, entity types, and permissions across workspaces and teams. It offers connectors for Slack, Notion, Google Drive, file stores, and S3-style buckets, enabling unified ingestion and incremental updates without rebuilding or manual reformatting. Cognee delivers cited retrieval and structured search that combine text snippets with graph facts, improving answer accuracy and auditability for customer-facing or regulated workflows. A workspace shows connected sources, entity and document counts, and a graph explorer, while an agent query returns cited snippets and structured facts through the memory API under workspace permissions.
Key features
- Converts documents, chats, and data sources into a graph memory for persistent recall
- Integrates via MCP and SDKs for agent compatibility without bespoke glue code
- Supports custom ontologies and schemas for domain-specific modeling
- Provides connectors for Slack, Notion, Google Drive, file stores, and S3-style buckets
- Delivers cited retrieval and structured search combining text snippets with graph facts
- Includes workspace dashboards for connected sources, entities, and graph exploration
- Scales from local installs to managed Cognee Cloud for multi-workspace deployment
- Enables incremental ingestion and updates without manual reformatting
- Offers permission controls and governance across workspaces and teams
- Provides a graph explorer for visualizing entities and relationships
Use cases
- Retain project context for coding agents so refactors, decisions, and fixes persist between runs
- Unify deals, accounts, and ICP notes into a searchable memory graph for revenue teams
- Turn technical manuals and SOPs into entity-linked answers with citations for support and field operations
Pros
- Open-source platform with local model support, enabling self-hosted deployments
- Unified memory layer for agents across sessions, preventing redundant work
- Structured graph-based memory with custom ontologies for domain-specific alignment
- Cited retrieval and auditability for regulated or customer-facing workflows
- Broad integration ecosystem including Slack, GitHub, Linear, Notion, and cloud storage
Cons
- Requires technical setup for local deployment and configuration
- Graph-based memory may introduce complexity for simple use cases
- Dependency on MCP-compatible agents for full functionality
Frequently asked questions about Cognee
What is Cognee and what problem does it solve?
Cognee is an open-source memory platform that provides durable, cited memory for AI agents across sessions. It solves the problem of agents losing context or repeating work by connecting scattered knowledge into a unified, recallable memory layer.
Who should use Cognee?
Cognee suits agent builders, teams, and enterprises that need persistent agent memory, domain-specific rule adherence, or unified knowledge retrieval across tools like Slack, GitHub, and Notion.
How does Cognee integrate with existing workflows?
Cognee integrates via MCP and SDKs, with first-party support for agents like Claude Code and LangGraph. It also offers connectors for common data sources such as Slack, GitHub, Linear, and cloud storage.
Can Cognee be deployed on-premises or in the cloud?
Yes, Cognee supports both local installations and managed cloud deployments, allowing teams to run it in their own infrastructure or use Cognee Cloud.
Does Cognee support customization of memory structure?
Yes, Cognee allows custom ontologies and schemas to model domains precisely, aligning memory with business rules, entity types, and permissions across workspaces.
How do agents interact with Cognee memory?
Agents read and write to Cognee memory through MCP or SDK calls, retrieving cited snippets and structured facts while preserving context and audit trails for improved accuracy.
Cognee traffic & engagement
cognee.ai · third-party estimates from Similarweb
Data as of Sep 2026Full AI website ranking →
Monthly visits · Sep 2026160K+36.1% MoM12-month high 160K (Sep 2026)
Rank among AI websites#1,551▲ 249 vs last monthof 8,652 tools on aitoolnavio™
Top marketUnited States24.2%Top 5 countries bring 56% of visits
Average visit1m 59sLonger than 76% of AI sites
Pages per visit2.92More than 77% of AI sites
Bounce rate38%Lower than 53% of AI sites
Similarweb global rank#242,685#54,101 in India
Traffic trend
Last 4 months · grows by one month every month
- Jun 2026118K
- Jul 2026158K+33.9%
- Aug 2026118K−25.7%
- Sep 2026160K+36.1%
Where visitors come from
Share of visits by channel
No measurable traffic from Paid Referrals.
Top countries
Share of visits · estimated visits
Other countries: 43.6%
Visits sent by AI assistants
How people reach this site from other AI tools
694 a month · 0.4% of all visits
Compared with similar tools
Automation & Agents · Sep 2026
Traffic figures are third-party estimates, good for scale and trends; they can differ from a company's own numbers. Updated monthly.
