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Add persistent memory to Cursor with the Mem0 MCP server. Your AI assistant forgets everything between sessions. Mem0 fixes that by connecting Cursor to Mem0’s cloud memory layer via MCP so you can save and retrieve relevant context during coding sessions.

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Prerequisites

Before setting up Mem0 with Cursor, ensure you have:
  1. A Mem0 Platform account and API key:
  2. Cursor installed (cursor.com)
  3. Your API key added to your shell profile (persists across sessions): 
echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.zshrc
source ~/.zshrc

echo 'export MEM0_API_KEY="m0-your-api-key"' >> ~/.bashrc
source ~/.bashrc
Already have mem0 configured as an MCP server in Cursor? Remove the existing entry from your Cursor MCP settings before installing to avoid duplicate tools.

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Installation

The fastest way to get started. Click the link below to install the Mem0 MCP server directly in Cursor: Install Mem0 MCP in Cursor

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Option B: npx (MCP Only)

npx mcp-add \
  --name mem0-mcp \
  --type http \
  --url "https://mcp.mem0.ai/mcp/" \
  --clients "cursor"

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Option C: Manual Configuration (MCP Only)

Add the following to your .cursor/mcp.json: 
{
  "mcpServers": {
    "mem0": {
      "url": "https://mcp.mem0.ai/mcp/",
      "headers": {
        "Authorization": "Token ${env:MEM0_API_KEY}"
      }
    }
  }
}
Start a new Cursor session and ask: “List my mem0 entities” or “Search my memories for hello”. If the mem0 tools appear and respond, you’re all set.

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Available MCP Tools

Once installed, the following tools are available in every Cursor session:
ToolDescription
add_memorySave text or conversation history for a user/agent
search_memoriesSemantic search across memories with filters
get_memoriesList memories with filters and pagination
get_memoryRetrieve a specific memory by ID
update_memoryOverwrite a memory’s text by ID
delete_memoryDelete a single memory by ID
delete_all_memoriesBulk delete all memories in scope
delete_entitiesDelete a user/agent/app/run entity and its memories
list_entitiesList users/agents/apps/runs stored in Mem0

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Example Workflow

# Session 1: Debugging a performance issue
You: The API endpoint /users is taking 3 seconds. Help me optimize it.

# Cursor agent searches memories, proceeds with investigation.
# After completing the task, Mem0 stores:
#   - Learning: "N+1 query in UserService.getAll(): fixed with eager loading"
#   - Decision: "Added database index on users.email column"
#   - Preference: "User prefers query-level fixes over caching"

# Session 2 (next week): Similar issue
You: The /orders endpoint is also slow, same pattern as before.

# Agent searches memories, retrieves the optimization learnings.
# Immediately checks for N+1 queries and missing indexes.

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Troubleshooting

  • “Connection failed”: Verify MEM0_API_KEY is set: echo $MEM0_API_KEY
  • Duplicate tools: If you had a previous MCP config for mem0, remove it before installing the plugin
  • No tools appearing: Go to Cursor Settings > MCP and verify the mem0 server shows as connected

Mem0 MCP Setup

Detailed MCP configuration for all clients
https://mintcdn.com/mem0/QK-8_hblyHgAr7vt/images/provider-icons/anthropic.svg?fit=max&auto=format&n=QK-8_hblyHgAr7vt&q=85&s=d2a2af9f60f53e9f21d741fe237af0f5

Claude Code Integration

Add Mem0 memory to Claude Code workflows
Using Mem0? Star us on GitHub to help more developers discover memory for AI apps.