ーを検索して発見しましょう。"}],["$","meta","17",{"name":"twitter:image","content":"https://mcp.so/logo.png"}]],"error":null,"digest":"$undefined"} e:{"metadata":"$14:metadata","error":null,"digest":"$undefined"} 28:I[60719,["7626","static/chunks/f6ab4fea-4425dae3da7674a3.js","8548","static/chunks/b27dc69b-e5acb70cd9d66ddf.js","5232","static/chunks/5232-db5923cda78a4960.js","6465","static/chunks/6465-6b79f1dc957ae3f4.js","9388","static/chunks/9388-d1a745fd53a10850.js","4902","static/chunks/4902-40271c136eb736f1.js","1508","static/chunks/1508-abbc58115cbb4fd0.js","6125","static/chunks/6125-6f7cbc86df4f2503.js","7771","static/chunks/7771-66979ce602088329.js","7660","static/chunks/7660-f5d56ac6a9ee6cc8.js","4147","static/chunks/4147-ef3df161a800b88b.js","9783","static/chunks/9783-e1d5b54e9718b38b.js","8084","static/chunks/8084-f1229cc5d0501fe0.js","2024","static/chunks/2024-e03e13f5faa34f45.js","7796","static/chunks/app/%5Blocale%5D/(default)/server/%5Bname%5D/%5Bauthor_name%5D/page-c3a3facf548ee943.js"],"default"] 29:T3728,

Graphiti

Build Real-Time Knowledge Graphs for AI Agents

[![Lint](https://github.com/getzep/Graphiti/actions/workflows/lint.yml/badge.svg?style=flat)](https://github.com/getzep/Graphiti/actions/workflows/lint.yml) [![Unit Tests](https://github.com/getzep/Graphiti/actions/workflows/unit_tests.yml/badge.svg)](https://github.com/getzep/Graphiti/actions/workflows/unit_tests.yml) [![MyPy Check](https://github.com/getzep/Graphiti/actions/workflows/typecheck.yml/badge.svg)](https://github.com/getzep/Graphiti/actions/workflows/typecheck.yml) ![GitHub Repo stars](https://img.shields.io/github/stars/getzep/graphiti) [![Discord](https://dcbadge.vercel.app/api/server/W8Kw6bsgXQ?style=flat)](https://discord.com/invite/W8Kw6bsgXQ) [![arXiv](https://img.shields.io/badge/arXiv-2501.13956-b31b1b.svg?style=flat)](https://arxiv.org/abs/2501.13956) [![Release](https://img.shields.io/github/v/release/getzep/graphiti?style=flat&label=Release&color=limegreen)](https://github.com/getzep/graphiti/releases)

: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

Graphiti

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