Integrations
MCP, Claude, LangChain, LlamaIndex, SDKs and frameworks.
Memory for every agent your team uses
A knowledge worker's agents don't share what they know: Claude and ChatGPT often can't reach company context, and the agents you build never see what Claude and ChatGPT learn. The Memory MCP Server gives each user one agent memory across all of them, governed by policy.
Coding agents can design your Zep implementation
Zep now ships one plugin for Claude Code, Codex, and Cursor. It gives your coding agent the Zep documentation MCP server and the new building-with-zep skill, which encodes how to design and evaluate an agent memory implementation around the use case you need to deliver.
Unified agent memory in any MCP client
Your team's agents are split across surfaces: the desktop assistant, the coding tool, the agents you build in-house. Each keeps its own memory or none at all. The Memory MCP Server puts them on one governed user graph, gated by your enterprise single sign-on.
Evaluation and Control: Evaluation Framework, zepctl CLI, and Dashboard Overhaul
An evaluation framework for testing Zep against your data, a redesigned dashboard with analytics, and zepctl — a CLI for administering Zep projects.
Building Voice Agents with Memory: Zep x LiveKit
Create personalized voice agents with long-term memory with minimal added latency
Graphiti Hits 20K Stars! + MCP Server 1.0
Graphiti crossed 20,000 GitHub stars today! Thanks for building with us.
Graphiti Adds FalkorDB Support as Project Approaches 14,000 Stars
FalkorDB contributes integration to Graphiti. Project approaching 14K stars & 25K weekly PyPI downloads.
Cursor IDE: Adding Memory With Graphiti MCP 🤖⚡️
Upgrade Cursor with persistent memory using Graphiti MCP. Now your favorite AI coding agent remembers your preferences, standards, and specs across sessions.
Building a Memory Agent with the OpenAI Agents SDK and Zep
A video walkthrough demonstrating using Zep's agent memory and the new OpenAI Agents SDK to build an AI agent with long-term memory.
ICYMI: Zep Vector DB, User Store, LlamaIndex support & more!
Wow, despite the great August weather in California 🌴☀️, we shipped a ton of good stuff 🚀. Here's the run-down in case you missed it.
Foundations of LLM App Building in TypeScript
Learn how to build three foundational LLM apps using TypeScript, LangChain.js, and Zep.
Announcing Anthropic Claude Support! 🎉
Zep v0.10.0, released today, supports Anthropic's Claude family of LLMs for summarization and extraction tasks.
Zep ❤️ LlamaIndex: A Vector Store Walkthrough
LlamaIndex is a simple but powerful framework for building LLM apps. It's also an excellent tool for populating and searching Zep's Vector Store. This walkthrough demonstrates using LlamaIndex's new ZepVectorStore to do just that.
ICYMI: Zep X Langchain, Session Metadata, and more 🔥⚡️
July was a busy month at Zep! Just in case you missed anything, here's a roundup.
Diagnosing and Fixing Slow Chatbots with LangSmith and Zep
Poor chatbot response times can result in frustrated users and churn. Langchain’s new LangSmith service makes it easy to diagnose the cause of latency in an LLM app. In this article, we use LangSmith to analyze a very slow Langchain app and improve performance by an order of magnitude using Zep.
Improved Langchain Support!
Langchain now includes improved support for Zep, with a new ZepMemory class, access to enriched messages, and more.
Goodbye Web Forms, Hello Chat Messages
A Guide to Using OpenAI Functions and Langchain to Extract Structured Data from LLM App Conversations
Semantic Similarity as an Intent Router for LLM Apps
Ensuring your LLM app understands user intent is crucial in offering a great experience. We build an intent router using Langchain, which automatically selects the prompt best suited to a task.
New Features: JWT Authentication, Azure OpenAI APIs, & Configurable Hard Deletion
Zep now supports JWT Authentication, Azure OpenAI APIs and OpenAI OrgIDs, and a configurable, periodic purge of soft-deleted data.
Introducing Intents
Zep's Intent Extractor identifies the intent of a message, persisting this to message metadata. 💡 With intent data, developers can build richer, more personalized agent interactions. 🔥
Introducing Zep Hybrid Search and Custom Metadata
Zep now supports both vector search over message text and filtering on message metadata, including system metadata such as Named Entities and creation dates.
LangchainJS Now Supports Zep!
LangchainJS now supports Zep Memory and Retrievers, allowing developers to take advantage of Zep's long-term memory, auto-summarization, vector search, and named entity extraction.
Introducing Zep: Long-term Memory Storage and Enrichment for AI Apps
Zep allows developers to focus on developing their AI apps, rather than building memory persistence, search, and enrichment infrastructure.
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