topoteretes/cognee
🔌 MCP Servertopoteretes
An advanced memory management framework for AI agents, supporting multi-source data ingestion and graph-based retrieval.
Cognee serves as the cognitive layer for AI agents, bridging the gap between raw data and actionable intelligence. At its core, it functions as a memory manager that transforms unstructured data into a structured knowledge graph, complemented by vector embeddings for semantic search. This dual-approach allows agents to perform both precise fact retrieval and broad contextual reasoning. The framework is highly modular, supporting integration with various vector databases and graph stores, ensuring flexibility for different infrastructure needs. The Cognee MCP server implementation specifically allows LLMs to interact with this memory layer through standard protocols, enabling agents to 'remember' user interactions, document contents, and historical data across sessions. By automating the ingestion, chunking, and graph-linking process, Cognee significantly reduces the overhead of building context-aware AI applications, making it a critical component for developers building complex, long-running agentic systems.
💡Highlights
- ├─Supports 30+ data sources
- ├─Graph and vector store integration
- └─Standardized MCP server interface
🎯For
- ├─AI Engineers
- └─Agent Developers