Docs Update (#2591)

2025-04-29 08:15:25 -07:00
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--- a/docs/integrations/agno.mdx
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 title: Agno
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+<Snippet file="paper-release.mdx" />

 Integrate [**Mem0**](https://github.com/mem0ai/mem0) with [Agno](https://github.com/agno-agi/agno), a Python framework for building autonomous agents. This integration enables Agno agents to access persistent memory across conversations, enhancing context retention and personalization.

--- a/docs/integrations/autogen.mdx
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 Build conversational AI agents with memory capabilities. This integration combines AutoGen for creating AI agents with Mem0 for memory management, enabling context-aware and personalized interactions.

+<Snippet file="paper-release.mdx" />
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 ## Overview

 In this guide, we'll explore an example of creating a conversational AI system with memory:
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 title: CrewAI
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+<Snippet file="paper-release.mdx" />
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 Build an AI system that combines CrewAI's agent-based architecture with Mem0's memory capabilities. This integration enables persistent memory across agent interactions and personalized task execution based on user history.

 ## Overview
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 title: Dify
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+<Snippet file="paper-release.mdx" />
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 # Integrating Mem0 with Dify AI

 Mem0 brings a robust memory layer to Dify AI, empowering your AI agents with persistent conversation storage and retrieval capabilities. With Mem0, your Dify applications gain the ability to recall past interactions and maintain context, ensuring more natural and insightful conversations.
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 title: ElevenLabs
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+<Snippet file="paper-release.mdx" />
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 Create voice-based conversational AI agents with memory capabilities by integrating ElevenLabs and Mem0. This integration enables persistent, context-aware voice interactions that remember past conversations.

 ## Overview
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 title: Flowise
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+<Snippet file="paper-release.mdx" />
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 The [**Mem0 Memory**](https://github.com/mem0ai/mem0) integration with [Flowise](https://github.com/FlowiseAI/Flowise) enables persistent memory capabilities for your AI chatflows. [Flowise](https://flowiseai.com/) is an open-source low-code tool for developers to build customized LLM orchestration flows & AI agents using a drag & drop interface.

 ## Overview
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 title: Keywords AI
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+<Snippet file="paper-release.mdx" />
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 Build AI applications with persistent memory and comprehensive LLM observability by integrating Mem0 with Keywords AI.

 ## Overview
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 description: 'Integrate Mem0 with LangChain tools to enable AI agents to store, search, and manage memories through structured interfaces'
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+<Snippet file="paper-release.mdx" />
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 ## Overview

 Mem0 provides a suite of tools for storing, searching, and retrieving memories, enabling agents to maintain context and learn from past interactions. The tools are built as Langchain tools, making them easily integrable with any AI agent implementation.
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 title: Langchain
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 Build a personalized Travel Agent AI using LangChain for conversation flow and Mem0 for memory retention. This integration enables context-aware and efficient travel planning experiences.

 ## Overview
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 title: LangGraph
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 Build a personalized Customer Support AI Agent using LangGraph for conversation flow and Mem0 for memory retention. This integration enables context-aware and efficient support experiences.

 ## Overview
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 title: Livekit
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 This guide demonstrates how to create a memory-enabled voice assistant using LiveKit, Deepgram, OpenAI, and Mem0, focusing on creating an intelligent, context-aware travel planning agent.

 ## Prerequisites
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 title: LlamaIndex
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 LlamaIndex supports Mem0 as a [memory store](https://llamahub.ai/l/memory/llama-index-memory-mem0). In this guide, we'll show you how to use it.

 <Note type="info">
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 title: MCP Server
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 ## Integrating mem0 as an MCP Server in Cursor
 [mem0](https://github.com/mem0ai/mem0-mcp) is a powerful tool designed to enhance AI-driven workflows, particularly in code generation and contextual memory. In this guide, we'll walk through integrating mem0 as an **MCP (Model Context Protocol) server** within [Cursor](https://cursor.sh/), an AI-powered coding editor.

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 title: MultiOn
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+<Snippet file="paper-release.mdx" />
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 Build a personal browser agent that remembers user preferences and automates web tasks. It integrates Mem0 for memory management with MultiOn for executing browser actions, enabling personalized and efficient web interactions.

 ## Overview
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 description: 'Integrate Mem0 with Pipecat for conversational memory in AI agents'
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+<Snippet file="paper-release.mdx" />
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 # Pipecat Integration

 Mem0 seamlessly integrates with [Pipecat](https://pipecat.ai), providing long-term memory capabilities for conversational AI agents. This integration allows your Pipecat-powered applications to remember past conversations and provide personalized responses based on user history.
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 title: Vercel AI SDK
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+<Snippet file="paper-release.mdx" />
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 The [**Mem0 AI SDK Provider**](https://www.npmjs.com/package/@mem0/vercel-ai-provider) is a library developed by **Mem0** to integrate with the Vercel AI SDK. This library brings enhanced AI interaction capabilities to your applications by introducing persistent memory functionality.

 <Note type="info">