Cognee
Open-source memory platform for AI agents. Capture context, turn it into graph memory, and let agents recall across sessions. Start local, scale to cloud.
Editor's Verdict
Key Takeaways
- Graph Memory for Agents
- Agentic Integrations
- Custom Ontologies
- Permissions Control
In-Depth Review: What is Cognee?
Cognee is an open-source memory platform that gives AI agents durable, cross-session recall. It ingests data from various sources, builds graph memories, and integrates with agents like Claude Code, Codex, and MCP. Use it for second brains, sales intelligence, documentation, and coding agents. Start locally with 'pip install cognee' and scale to Cognee Cloud for production.
Core Features
Graph Memory for Agents
Capture context and turn it into graph memory that any agent can recall across sessions, improving continuity and accuracy.
Agentic Integrations
First-party integrations with Claude Code, Codex, LangGraph, OpenClaw, and MCP server for seamless memory read/write.
Custom Ontologies
Define custom ontologies and data models to tailor memory to your domain.
Permissions Control
Govern access to memory with fine-grained permissions, ensuring data security.
Data Source Adapters
Connect data from warehouses, docs, chats, and APIs into a unified recallable memory layer.
Local to Cloud Scaling
Start locally with open source and scale to Cognee Cloud for managed infrastructure.
Pricing
Free
- 1 workspace
- 1M tokens included
- Unlimited users
- Unlimited API calls
- Agentic integrations (Claude Code, Codex, MCP)
Standard
- Pay only for tokens processed
- Unlimited workspaces ($5 each per month)
- Data source integrations: Slack, Notion, Google Drive
- In-app support
Enterprise
- Dedicated Slack channel
- Dedicated support engineer
- BYO cloud supported
- Support SLA
Pros and Cons
Pros
- Open Source & Free to StartCognee is open source, allowing you to run the full memory engine locally or on your own stack at no cost.
- Seamless Agent IntegrationWorks out-of-the-box with popular AI agents like Claude Code, Codex, and MCP clients, reducing setup time.
- Graph Memory for Better RecallUses graph-based memory to capture relationships, improving context retention and accuracy across sessions.
- Scalable from Local to CloudStart locally with pip install, then scale to Cognee Cloud for managed production use.
- Customizable Memory StructureSupports custom ontologies and data models, adapting to specific domain needs.
Cons
- Limited Free Tier TokensFree plan includes only 1M tokens, which may be insufficient for heavy usage.
- Variable Token CostsStandard plan charges per token (2.50 USD per 1M tokens), leading to unpredictable costs for large workloads.
- No Yearly Discount OptionPricing is monthly only; no annual plan or discount is mentioned.
- Self-Hosting Requires Technical ExpertiseRunning Cognee on your own infrastructure requires knowledge of graph and vector databases.
- Advanced Features May Need SetupCustom ontologies and permissions control require configuration, which may add complexity.
Use Cases & Recommended Professions
AI Agent Developer→ View Toolkit
Build agents that retain context across sessions, improving user experience and reducing redundant learning.
Data Scientist / Researcher→ View Toolkit
Enhance research workflows with searchable, connected notes and data that agents can recall.
Sales Professional→ View Toolkit
Maintain deal intelligence and account history that team members and AI assistants can query.
Knowledge Manager→ View Toolkit
Create and manage technical knowledge bases that are easily queryable by agents.
Product Engineer→ View Toolkit
Ship customer-facing agents with accurate, cited answers and domain-specific memory.
Technical Writer→ View Toolkit
Build and maintain documentation that agents can reference, ensuring consistency and updates.
Frequently Asked Questions
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ℹ️ Curation Disclosure: The overview and features of Cognee were synthesized using AI and fact-checked by our curation team to ensure accuracy.
