AI Agent Index
ByHeather MacAvelia·Independently reviewed·Last verified Jun 29, 2026

Open-source AI memory platform for agents using hybrid graph and vector architecture. ECL pipeline. $7.5M seed, 24,900+ GitHub stars. Free self-hosted; Cloud from $5/workspace/mo.

How we scored it

Autonomy

4/5

Integrations

5/5

Pricing clarity

5/5

Evidence

3/5

Setup

5/5

The facts

Cognee is an open-source AI memory platform built by topoteretes, headquartered in Berlin, that transforms raw data into structured knowledge graphs for AI agents. Most memory systems store text chunks in a vector database. Cognee runs an ECL pipeline (Extract, Cognify, Load) that extracts entities, maps relationships, and builds a queryable knowledge graph with embeddings. This gives agents temporal awareness, entity relationships, and feedback loops that pure vector retrieval cannot provide. The core operations are four: remember (store to graph), recall (query with auto-routing), forget (delete), and improve (refine through feedback). When an agent rates a response, that feedback updates edge weights in the graph, so the memory gets sharper with use rather than staying static. Cognee unifies three storage layers (relational, vector, and graph) into a single engine using SQLite, LanceDB, and Kuzu locally, with managed cloud options for production scale. $7.5M seed raised in February 2026 from investors including former OpenAI and Facebook AI Research builders. Pipeline volume grew from 2,000 runs to over 1 million runs in 2025. 27.7k GitHub stars and 2.3k forks as of Q3 2026. In production at 70+ companies including Bayer for scientific research workflows. Graduated from the GitHub Secure Open Source Program and the Berkeley XCelerator program. Native integrations with Claude Agent SDK, OpenAI Agents SDK, LangGraph, Google ADK, n8n, Amazon Neptune, Neo4j, and more. Official MCP integration available via docs. Available as a Claude Code plugin. Pricing was restructured in 2026 to a token-based model with a flat rate of $2.50 per 1M tokens across all plans. Hobby is free at $0/month with 1M tokens included, unlimited users, unlimited API calls, and 1 workspace. Growth is $5/workspace/month with unlimited workspaces, data source integrations (Slack, Notion, Google Drive), and in-app support. Enterprise is custom-priced with dedicated support engineer, BYO cloud, and SLAs. Self-hosted deployment remains free. Graph features are available at every tier: unlike Mem0, which gates graph memory behind the $249/month Pro tier, Cognee provides full graph capabilities from the free tier. Who Cognee is not for: the Python-only SDK means TypeScript, Go, or other language-based agent stacks cannot use Cognee natively without custom wrappers, whereas Mem0 supports both Python and JavaScript. Teams that need a turn-key hosted memory solution with minimal setup may find Mem0 Cloud simpler to onboard. Teams requiring published temporal reasoning benchmarks for procurement comparison should note that Cognee has not published a LongMemEval score comparable to Mem0 (49%) or Hindsight (91.4%), making objective capability comparison harder. Alternatives: Mem0 for cross-language support and a larger community; Zep for structured user memory with session history; custom vector database solutions (Pinecone, Weaviate) for teams that do not need graph-based relationship mapping. Current state Q3 2026: Cognee has surpassed 5 million SDK runs per month and is in production at 70+ organizations including Bayer for scientific research workflows. Version 1.2.2 released. 27.7k GitHub stars with 2.3k forks. The official MCP server provides 14 specialized tools compatible with Claude Desktop, Cursor, Continue, Cline, and Roo Code. It supports both standalone mode for individual developers and API mode for teams sharing a single knowledge graph across multiple AI clients.

Pricing

freemium · $5/mo

View pricing ↗

Segment

b2b

Setup

moderate

Verified

Jun 29, 2026

Transparency

Public

Contract

Month-to-month

Data training

Not Disclosed

Autonomy

Autonomous

Capabilities

deep-researchdata-analysisautonomousweb-searchworkflow-builderbyok

Pros & Limitations

Editorial assessment

Pros

  • Knowledge graph available at every pricing tier including the free self-hosted tier. Unlike Mem0, which gates graph memory behind the $249/month Pro plan, Cognee gives teams full graph capabilities from day one without a paid upgrade.
  • ECL pipeline builds self-improving memory that gets sharper with use. Rated responses feed back into graph edge weights, so accuracy improves over time rather than staying static like vector-only systems.
  • Official MCP server with 14 specialized tools works with Claude Desktop, Cursor, Continue, Cline, and Roo Code. Supports both standalone mode for individual developers and API mode for teams sharing a single knowledge graph across multiple AI clients.

Limitations

  • Python-only SDK limits integration options. TypeScript, Go, or other language-based agent stacks cannot use Cognee natively, narrowing its addressable developer audience compared to Mem0 which supports both Python and JavaScript.
  • Smaller ecosystem than Mem0: 27.7k GitHub stars versus Mem0's 48,000+ means less community content, fewer pre-built examples, and a smaller pool of developers who have solved common integration problems.
  • No published LongMemEval benchmark score. Mem0 scores 49% and Hindsight scores 91.4% on temporal reasoning benchmarks, but Cognee has not published equivalent scores, making objective capability comparison difficult for procurement teams.

Technical Details

Deployment
cloudself-hosted
Model architectureOpen-source: hybrid graph and vector architecture, not a model
Avg setup time3-5 minutes
Autonomous rateAutonomously ingests unstructured data (documents, PDFs, web content), builds a knowledge graph, and surfaces connected insights without manual tagging or relationship mapping.
MCP compatibleYes
Integrations
LangGraphOpenAI Agents SDKClaude Agent SDKn8nNeo4jLanceDBQdrantPGVectorWeaviateAmazon NeptuneCursorClaude Code
Security
GDPR

Similar agents

Rating

4.1/ 5

Editorial score

How we score this →

Recognition

Transparent PricingListed 2026
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Industries

DevToolsSaaSEnterpriseB2BOpen Source

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