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Mem0 MCP, Ready to Go

Give your AI agents long-term memory with Mem0. Let Claude or Cursor remember user preferences and past context across every single session.

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Give your agent long-term memory to remember user preferences and past context.

Mem0 MCP for AI Agents

Works with every AI agent you already use

…and any MCP-compatible client

Cursor AI Code EditorClaude Desktop AppOpenAI Agents SDKVisual Studio CodeGitHub Copilot AI AgentGoogle Gemini AILovable AI DevelopmentMistral AI AgentsAmazon AWS Bedrock

How fast is the Mem0 Connector?

1025ms Fast
Fast Acceptable Slow

Average time for the server to become ready for requests over the last 14 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this Connector on Vinkius Cloud, and connect it to your AI agent in seconds.

Min 808ms
Average 1025ms
Max 1637ms
Trend (improving) ↓ 12%
Daily latency
959ms 11/07/2026
1637ms 12/07/2026
1061ms 13/07/2026
1046ms 14/07/2026
1252ms 15/07/2026
1055ms 16/07/2026
875ms 17/07/2026
882ms 18/07/2026
962ms 19/07/2026
952ms 20/07/2026
1000ms 21/07/2026
808ms 22/07/2026
1025ms 23/07/2026
1325ms 24/07/2026
11/07/2026 24/07/2026

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AI Agent

What AI agents can do with Mem0 MCP: 4 Tools for Persistent Agent Memory

Give your agent the ability to store, search, and recall user facts and preferences automatically.

Delete memory

Mem0 uses delete_memory to remove a specific memory by its ID when it's no longer accurate or needed. This helps keep your agent's knowledge base clean and relevant.

Get memories

Mem0 uses get_memories to list every stored memory for a specific user to build a full profile of their history. Use this to see exactly what your agent knows about a person.

Search memories

Mem0 uses search_memories to find the most relevant memories based on a natural language query from the user. This allows your agent to recall past facts and preferences instantly.

Add memory

Mem0 uses add_memory to save new facts and preferences from a conversation into the user's persistent memory profile. The system automatically extracts key details for you.

A Connector is a URL. Vinkius runs it: hosting, security, governance, observability.

You're looking at one of 5,800+ managed Connectors. The real value isn't the catalog. It's the control plane that secures, governs, audits, and manages every interaction between your agents and the tools they use.

01

No Shadow AI

Every agent action is visible, approved, and auditable. Nothing runs outside your governance.

02

Absolute agent control

Fine-grained permissions for every agent, MCP, and tool. Instantly revoke access and audit every execution.

03

Cost control per token

Spend broken down to the token, tool, and agent. Budgets and hard limits. No surprise invoices.

04

Managed & monitored infra

We operate the runtime, authentication, scaling, retries, and monitoring. Your team manages AI, not infrastructure.

05

Data protection, DLP by design

Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.

06

Token optimization, real savings

Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.

Mem0 MCP for Persistent Agent Memory and Personalization

This is for developers and product teams who are tired of building forgetful bots. It's for the person building a personalized SaaS experience where the AI needs to remember a user's style across weeks of interaction.

AI Agent Developer

Builds complex agents that need to remember past decisions without constant manual prompts.

Chatbot Builder

Creates high-touch customer service bots that remember a customer's previous issues and preferences.

SaaS Product Manager

Integrates persistent memory into a product so the AI feels like a long-term partner rather than a one-off tool.

Frequently Asked Questions

What is Mem0 MCP for AI agents? +

Mem0 MCP for AI agents provides a persistent memory layer. It lets your agent remember facts, preferences, and context from previous conversations so it can provide a personalized experience every time you talk to it.

How does Mem0 help with personalization? +

It stores specific user details automatically. When you tell your agent something about your workflow or preferences, it saves that info and recalls it during future sessions to make the AI feel more tailored to you.

Can my AI agent remember things across different sessions? +

Yes, that's the main goal. While most agents start fresh every time, this Connector allows your agent to pull from a permanent memory bank to keep track of your history and preferences indefinitely.

How do I keep the agent's memory from getting cluttered? +

You can manage the stored information easily. The system allows for the removal of specific memories, so you can delete outdated facts or incorrect information to keep the agent's context sharp.

Is Mem0 MCP for AI agents good for building user profiles? +

It's perfect for that. It allows you to view all stored memories for a specific user, making it easy to see exactly what the agent has learned about them and how it's building their unique profile.

Does Mem0 MCP for AI agents require a complex setup? +

No, it's designed to be a straightforward memory layer. Once you connect your API key to your AI client, the agent starts handling the memory extraction and storage automatically.

Is Mem0 free to use? +

Yes! Mem0 offers a free Hobby tier with 10,000 memories and 1,000 search calls per month — no credit card required. Paid plans start at $19/month for higher limits. An open-source version (Apache 2.0) is also available for self-hosting.

How does Mem0 extract and store memories? +

When you send content to Mem0, its AI automatically extracts key facts and structured information. For example, if you send 'I prefer Python over JavaScript and work best in the morning', Mem0 creates two separate memories: one about language preference and one about work schedule. These are stored in a hybrid architecture (key-value + vector + graph) for fast semantic retrieval.

Can I organize memories by user or agent? +

Yes! Every memory operation supports scoping by user_id, agent_id, or run_id. This means you can maintain separate memory banks for different users, different agents, or even different conversation runs — keeping context perfectly isolated.

Your AI, connected to everything.

No credit card required · Free tier available

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