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Introducing OpenMemory MCP

Backed by

The Memory Layer for your AI Agents

Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users.

Get Started

Try the Playground

Trusted by developers from

OUR CUSTOMER

Voices From the Field

How Sunflower Sober Scaled Personalized Recovery Support to 80,000+ Users with Mem0

Read Case Study

“Mem0 transformed our AI companion in just one day of integration, delivering personalized support that remembers user journeys and significantly reduced our costs. It's been one of our highest-ROI decisions.”

Engineering Lead, Sunflower Sober

How BrowserUse Achieved 98% Task Completion and 41% Cost Reduction with Mem0

Read Case Study

BrowserUse leverages Mem0’s procedural memory system, enabling long sequence tasks for browser agents and cutting cost by lowering token usage.

Magnus, CEO BrowserUse

Key features

What is Mem0

Mem0 remembers user preferences, adapts to individual needs, and continuously improves over time,

Learn more

Enhance Future Conversations

Build smarter AI that learns from every interaction, providing context-rich responses without repetitive questions.

Save Money

Reduce LLM costs by up to 80% through intelligent data filtering, sending only the most relevant information to AI models.

Improve AI Responses

Deliver more accurate and personalized AI outputs by leveraging historical context and user preferences.

Easy Integration

Seamlessly enhance your existing AI solutions with Mem0's memory layer - compatible with OpenAI, Claude, and more.

Use cases

Perfect For Your Project

We're developers building tools for developers. Our mission: to make AI applications that understand context and remember users, creating more natural and efficient interactions.

Customer Support
Customer Support

Enhance customer satisfaction with chatbots that remember past interactions, reducing repetition and speeding up resolution times

Enhance customer satisfaction with chatbots that remember past interactions, reducing repetition and speeding up resolution times

Personal AI Companion
Personal AI Companion

Create AI companions that truly know you, recalling preferences and past conversations for more meaningful interactions.

Create AI companions that truly know you, recalling preferences and past conversations for more meaningful interactions.

AI Agents
AI Agents

Develop smarter AI agents that learn from each interaction, becoming more personalized and effective over time

Develop smarter AI agents that learn from each interaction, becoming more personalized and effective over time

E-Commerce
E-Commerce

Increase sales with AI that remembers customer preferences, providing tailored product recommendations that feel personal

Increase sales with AI that remembers customer preferences, providing tailored product recommendations that feel personal

Two Powerful Ways

Leverage Mem0 Technology

Choose the integration that fits your needs: fully managed for convenience or self-hosted for complete control.

Mem0 Platform

Effortless Integration, Maximum Performance

Our fully managed platform offers a seamless way to enhance your AI applications with Mem0's memory capabilities. Ideal for teams looking for quick deployment and hassle-free maintenance.

Sign Up Now

Mem0 Open Source

Unlimited Customization, Complete Control

For teams that need full flexibility, our open-source version allows you to tailor Mem0 to your exact requirements. Self-host on your infrastructure for maximum data control and customization.

View GitHub Repository

QUICK-START

Get Started Today

Empower Your AI applications with Mem0's Intelligent Memory Layer in Minutes

View documentation

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from mem0 import MemoryClient

client = MemoryClient(api_key="your-api-key")

# Store user preference
client.add([
 {"role": "user", "content": "I love spicy food."},
 {"role": "assistant", "content": "Noted! You enjoy spicy cuisine."}
], user_id="user123")

# Later, retrieve and use the preference
query = "What food does the user like?"
memory = client.search(query, user_id="user123")
print(f"Retrieved: {memory}")
# Output: Retrieved: The user loves spicy food.

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from mem0 import MemoryClient

client = MemoryClient(api_key="your-api-key")

# Store user preference
client.add([
 {"role": "user", "content": "I love spicy food."},
 {"role": "assistant", "content": "Noted! You enjoy spicy cuisine."}
], user_id="user123")

# Later, retrieve and use the preference
query = "What food does the user like?"
memory = client.search(query, user_id="user123")
print(f"Retrieved: {memory}")
# Output: Retrieved: The user loves spicy food.

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from mem0 import MemoryClient

client = MemoryClient(api_key="your-api-key")

# Store user preference
client.add([
 {"role": "user", "content": "I love spicy food."},
 {"role": "assistant", "content": "Noted! You enjoy spicy cuisine."}
], user_id="user123")

# Later, retrieve and use the preference
query = "What food does the user like?"
memory = client.search(query, user_id="user123")
print(f"Retrieved: {memory}")
# Output: Retrieved: The user loves spicy food.

TESTIMONIALS

What Our Users Are Saying

Discover how Mem0 is transforming AI app development across industries. Our users share their experiences of enhanced performance, reduced costs, and improved user satisfaction.

  • Dominic Steil

    @domsteil

    Integrating Mem0 was incredibly easy and immediately enhanced the memory of our Agents. It has simplified the way we reason about personalization and the time to value is excellent.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Ali Madad

    @amadad

    @mem0ai is fantastic!

  • Amjad Raza (Ph.D)

    @maraza24

    Being a user of @mem0ai, it is super easy to setup and integrate with few commands. It’s a scalable solution to cater of larger conversation into smaller key facts and store those in your vector store.

  • Dhravya Shah

    @DhravyaShah

    Mem0 enhances our personalization capabilities, making our search feature top-notch and saving us thousands in engineering time every month.

  • Div Garg

    @DivGarg_

    Mem0 makes our browser agents more personalised and efficient. We saw a notable increase in usage and retention after integrating Mem0.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Braelyn

    @braelyn_ai

    Mem0 is actually pretty sick! Dynamic graph memory and so easy to implement. I am adding it to agentstack right now.

  • Wael Aridi

    @mindmergewa

    I've worked with mem0 too and I love how easy it is to integrate into my projects. Great choice adding it to agentstack!

  • Dominic Steil

    @domsteil

    Integrating Mem0 was incredibly easy and immediately enhanced the memory of our Agents. It has simplified the way we reason about personalization and the time to value is excellent.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Ali Madad

    @amadad

    @mem0ai is fantastic!

  • Amjad Raza (Ph.D)

    @maraza24

    Being a user of @mem0ai, it is super easy to setup and integrate with few commands. It’s a scalable solution to cater of larger conversation into smaller key facts and store those in your vector store.

  • Dhravya Shah

    @DhravyaShah

    Mem0 enhances our personalization capabilities, making our search feature top-notch and saving us thousands in engineering time every month.

  • Div Garg

    @DivGarg_

    Mem0 makes our browser agents more personalised and efficient. We saw a notable increase in usage and retention after integrating Mem0.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Braelyn

    @braelyn_ai

    Mem0 is actually pretty sick! Dynamic graph memory and so easy to implement. I am adding it to agentstack right now.

  • Wael Aridi

    @mindmergewa

    I've worked with mem0 too and I love how easy it is to integrate into my projects. Great choice adding it to agentstack!

  • Dominic Steil

    @domsteil

    Integrating Mem0 was incredibly easy and immediately enhanced the memory of our Agents. It has simplified the way we reason about personalization and the time to value is excellent.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Ali Madad

    @amadad

    @mem0ai is fantastic!

  • Amjad Raza (Ph.D)

    @maraza24

    Being a user of @mem0ai, it is super easy to setup and integrate with few commands. It’s a scalable solution to cater of larger conversation into smaller key facts and store those in your vector store.

  • Dhravya Shah

    @DhravyaShah

    Mem0 enhances our personalization capabilities, making our search feature top-notch and saving us thousands in engineering time every month.

  • Div Garg

    @DivGarg_

    Mem0 makes our browser agents more personalised and efficient. We saw a notable increase in usage and retention after integrating Mem0.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Braelyn

    @braelyn_ai

    Mem0 is actually pretty sick! Dynamic graph memory and so easy to implement. I am adding it to agentstack right now.

  • Wael Aridi

    @mindmergewa

    I've worked with mem0 too and I love how easy it is to integrate into my projects. Great choice adding it to agentstack!

  • Dominic Steil

    @domsteil

    Integrating Mem0 was incredibly easy and immediately enhanced the memory of our Agents. It has simplified the way we reason about personalization and the time to value is excellent.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Ali Madad

    @amadad

    @mem0ai is fantastic!

  • Amjad Raza (Ph.D)

    @maraza24

    Being a user of @mem0ai, it is super easy to setup and integrate with few commands. It’s a scalable solution to cater of larger conversation into smaller key facts and store those in your vector store.

  • Dhravya Shah

    @DhravyaShah

    Mem0 enhances our personalization capabilities, making our search feature top-notch and saving us thousands in engineering time every month.

  • Div Garg

    @DivGarg_

    Mem0 makes our browser agents more personalised and efficient. We saw a notable increase in usage and retention after integrating Mem0.

  • Lior

    @AlphaSignalAI

    It's a new memory layer for LLMs that allows you to directly add, update, and search memories in your models. It's crucial for AI systems that require persistent context, like customer support and personalized recommendations.

  • Braelyn

    @braelyn_ai

    Mem0 is actually pretty sick! Dynamic graph memory and so easy to implement. I am adding it to agentstack right now.

  • Wael Aridi

    @mindmergewa

    I've worked with mem0 too and I love how easy it is to integrate into my projects. Great choice adding it to agentstack!

FAQ

Frequently Asked Questions

Still have questions?

Get in Touch

What is the difference between Mem0 Open-Source and Platform?

What is the pricing?

How do I get started?

What is the difference between Mem0 Open-Source and Platform?

What is the pricing?

How do I get started?

Add Memory to Your AI Apps,
in a weekend

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© 2024 Mem0. All rights reserved.

Home

Pricing

GitHub

Community

Blog

Docs

Status

Privacy Policy

© 2024 Mem0. All rights reserved.

Home

Pricing

GitHub

Community

Blog

Docs

Status

Privacy Policy

© 2024 Mem0. All rights reserved.

Give your AI a memory and personality.

Instant memory for LLMs—better, cheaper, personal.

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Give your AI a memory and personality.

Instant memory for LLMs—better, cheaper, personal.

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Give your AI a memory and personality.

Instant memory for LLMs—better, cheaper, personal.

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Get Started

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