Mem0 Connector for AI agents.
4 live capabilities
Give your agent long-term memory to remember user preferences and past context.
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Why people use Mem0
Mem0 for Persistent Agent Memory and Personalization
Mem0 changes that by giving your agent a permanent place to store what it learns. When a user shares a preference, the agent saves it to a long-term profile. The next time you open the app, the agent already knows who you are and how you like to work. You get a capability that actually builds a relationship with the user over time.
What Vinkius changes
Your agent stops forgetting who it's talking to and starts remembering every detail that matters.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
User prefers dark mode
A user tells an agent they like dark mode.
- Real-world use case 02
Coding preferences
A developer mentions they use TypeScript.
- Real-world use case 03
Customer Support
A customer complains about a recurring bug.
Complete set · 4capabilities
The complete Mem0 capability set.
These are the exact actions your AI can choose when you ask it to work with Mem0.
01—04
4 capabilities in this set.
Part of 4 available through Mem0.
- 01 Capability
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.
- 02 Capability
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.
- 03 Capability
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.
- 04 Capability
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.
Set up in minutes
One URL. Then ask Mem0 to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Mem0 from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_G1YeH4ndKkDjNcv9DrC9WaHAUopRWaqhaZNb5wse/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Mem0, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Mem0 for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_G1YeH4ndKkDjNcv9DrC9WaHAUopRWaqhaZNb5wse/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Mem0 URL.
- Step 03
Save and start
Save the connection and enable Mem0 in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"mem0": {
"url": "https://edge.vinkius.com/vk_preview_G1YeH4ndKkDjNcv9DrC9WaHAUopRWaqhaZNb5wse/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Mem0
Open Agent mode in chat and ask: "Using Mem0, help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"mem0": {
"url": "https://edge.vinkius.com/vk_preview_G1YeH4ndKkDjNcv9DrC9WaHAUopRWaqhaZNb5wse/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Mem0
Ask Copilot: "Using Mem0, help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"mem0": {
"url": "https://edge.vinkius.com/vk_preview_G1YeH4ndKkDjNcv9DrC9WaHAUopRWaqhaZNb5wse/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Mem0
Open Cascade and ask: "Using Mem0, help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"mem0": {
"url": "https://edge.vinkius.com/vk_preview_G1YeH4ndKkDjNcv9DrC9WaHAUopRWaqhaZNb5wse/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Mem0
Ask Cline: "Using Mem0, help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add mem0 --transport http "https://edge.vinkius.com/vk_preview_G1YeH4ndKkDjNcv9DrC9WaHAUopRWaqhaZNb5wse/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Mem0
Ask Claude: "Using Mem0, show me...". 4 tools are ready
Where the request belongs
Work Mem0 can move forward.
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 capability.
When one Connector is not enough
Carry the request into a workflow.
Combine Mem0 with the systems that finish the task.
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You had a critical decision in a meeting 3 weeks ago but nobody remembers the exact reasoning , Deepgram transcribes every meeting, Mem0 stores decisions with persistent memory, and Sheets tracks all commitments
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsMem AI (Knowledge Workspace)
Manage your knowledge base via Mem.ai. create notes, run AI semantic search, and organize collections.
Botsonic
Train custom AI chatbots on your own data to deliver instant, accurate support that learns from your knowledge base.
VectorShift (AI Workflow & RAG Automation)
Automate AI workflows and RAG via VectorShift. manage pipelines, query knowledge bases, and deploy chatbots directly from any AI agent.
Cognita (RAG Framework)
Manage modular RAG via Cognita. list collections, ingest data sources, and perform AI-driven Q&A directly from any AI agent.
FastGPT
Manage FastGPT Knowledge Bases. automate dataset creation, document ingestion, and RAG search directly from any AI agent.
Capacities
Empower your AI agents to build knowledge graphs, append daily notes, and save weblinks directly into your Capacities spaces.
Bring your own AI
Change the model, client or framework. Keep Mem0 connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Mem0.
The practical details behind the request, access and result.
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.
One connection away
Give your agent a direct line to Mem0.
Connect Mem0 once. Keep it beside 5,900+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available