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Add persistent memory to OpenAI Codex with the Mem0 plugin. Codex forgets everything between tasks — this plugin fixes that by connecting to Mem0’s cloud memory layer via MCP and using a skill-based memory protocol to automatically retrieve context and store learnings.

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Overview

  1. MCP Server — Connect to Mem0’s remote MCP server for memory tools (add, search, update, delete)
  2. Memory Protocol Skill — Instructs the agent to retrieve memories at task start, store learnings on completion, and capture session state before context loss
  3. Plugin Marketplace — Install via Codex’s repo-level or personal plugin marketplace
  4. Zero local dependencies — Cloud-hosted MCP server, no local setup required

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Prerequisites

Before setting up Mem0 with Codex, ensure you have:
  1. A Mem0 Platform account and API key:
  2. OpenAI Codex access
  3. Your API key exported in your shell: 
export MEM0_API_KEY="m0-your-api-key"

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Installation

Add a .agents/plugins/marketplace.json to your repository root: 
{
  "name": "mem0-plugins",
  "interface": {
    "displayName": "Mem0 Plugins"
  },
  "plugins": [
    {
      "name": "mem0",
      "source": {
        "source": "local",
        "path": "./plugins/mem0"
      },
      "policy": {
        "installation": "AVAILABLE",
        "authentication": "ON_INSTALL"
      },
      "category": "Productivity"
    }
  ]
}
Then in Codex, browse the repo’s plugin directory and install Mem0.

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Option B — Personal Marketplace

Add to ~/.agents/plugins/marketplace.json: 
{
  "name": "mem0-plugins",
  "interface": {
    "displayName": "Mem0 Plugins"
  },
  "plugins": [
    {
      "name": "mem0",
      "source": {
        "source": "local",
        "path": "/path/to/mem0-plugin"
      },
      "policy": {
        "installation": "AVAILABLE",
        "authentication": "ON_INSTALL"
      },
      "category": "Productivity"
    }
  ]
}

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Option C — Manual MCP Configuration

Add to your Codex MCP config: 
{
  "mcpServers": {
    "mem0": {
      "type": "http",
      "url": "https://mcp.mem0.ai/mcp/",
      "headers": {
        "Authorization": "Token ${MEM0_API_KEY}"
      }
    }
  }
}
Start a new Codex task 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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What’s Included

ComponentPlugin InstallMCP Only
MCP Server (9 memory tools)YesYes
Memory Protocol SkillYesNo
Mem0 SDK SkillYesNo

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Available MCP Tools

Once installed, the following tools are available in every Codex 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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Memory Protocol Skill

Codex uses a skill-based approach instead of lifecycle hooks. When installed via the plugin marketplace, the memory protocol skill instructs the agent to:

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On Every New Task

  1. Call search_memories with a query related to the current task to load relevant context
  2. Review returned memories to understand what was learned in prior sessions
  3. Optionally call get_memories to browse all stored memories

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After Completing Significant Work

Store key learnings using add_memory with structured metadata:
What to storeMetadata type
Architectural decisions{"type": "decision"}
Strategies that worked{"type": "task_learning"}
Failed approaches{"type": "anti_pattern"}
User preferences observed{"type": "user_preference"}
Environment discoveries{"type": "environmental"}
Conventions established{"type": "convention"}

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Before Losing Context

Store a comprehensive session summary including goals, accomplishments, decisions, files modified, and current state with metadata {"type": "session_state"}.

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Plugin Manifest

The Codex plugin manifest (.codex-plugin/plugin.json) follows the Codex plugin specification: 
{
  "name": "mem0",
  "version": "0.1.0",
  "description": "Mem0 memory layer for AI applications.",
  "skills": "./skills/",
  "mcpServers": "./.codex-mcp.json",
  "interface": {
    "displayName": "Mem0",
    "shortDescription": "Persistent memory layer for AI coding workflows",
    "category": "Productivity",
    "capabilities": ["Read", "Write"]
  }
}

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Example Workflow

# Task 1: Setting up a new service
You: Create a REST API for the notifications service using Express and TypeScript.

# Codex searches memories, finds user preferences from prior tasks.
# After completing the task, Mem0 stores:
#   - Decision: "Notifications service uses Express + TypeScript + Zod validation"
#   - Convention: "All API routes follow /api/v1/{resource} pattern"
#   - Preference: "User prefers explicit error types over generic catch-all"

# Task 2 (days later): Extending the service
You: Add WebSocket support for real-time notification delivery.

# Codex searches memories, retrieves the architecture decisions and conventions.
# Follows the same patterns established in the first task.

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Troubleshooting

  • “Connection failed” — Verify MEM0_API_KEY is set in your shell: echo $MEM0_API_KEY
  • No tools appearing — Restart your Codex session after plugin installation
  • Plugin not found — Ensure .agents/plugins/marketplace.json is at the repository root and source.path points to the correct plugin directory
  • Skills not loading — Verify the skills field in plugin.json points to a valid directory containing SKILL.md files

Mem0 MCP Setup

Detailed MCP configuration for all clients

Claude Code Integration

Add Mem0 memory to Claude Code workflows