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Graphiti

Build Real-Time Knowledge Graphs for AI Agents

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:star: _Help us reach more developers and grow the Graphiti community. Star this repo!_
> [!TIP] > Check out the new [MCP server for Graphiti](mcp_server/README.md)! Give Claude, Cursor, and other MCP clients powerful Knowledge Graph-based memory. Graphiti is a framework for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents operating in dynamic environments. Unlike traditional retrieval-augmented generation (RAG) methods, Graphiti continuously integrates user interactions, structured and unstructured enterprise data, and external information into a coherent, queryable graph. The framework supports incremental data updates, efficient retrieval, and precise historical queries without requiring complete graph recomputation, making it suitable for developing interactive, context-aware AI applications. Use Graphiti to: - Integrate and maintain dynamic user interactions and business data. - Facilitate state-based reasoning and task automation for agents. - Query complex, evolving data with semantic, keyword, and graph-based search methods.

Graphiti temporal walkthrough

A knowledge graph is a network of interconnected facts, such as _"Kendra loves Adidas shoes."_ Each fact is a "triplet" represented by two entities, or nodes ("Kendra", "Adidas shoes"), and their relationship, or edge ("loves"). Knowledge Graphs have been explored extensively for information retrieval. What makes Graphiti unique is

#graphiti

Graphiti