@pinkpixel/mem0-mcp MCP Server ✨

A Model Context Protocol (MCP) server that integrates with Mem0.ai to provide persistent memory capabilities for LLMs. It allows AI agents to store and retrieve information across sessions.

This server uses the mem0ai Node.js SDK for its core functionality.

Features 🧠

Modernized & Advanced Tools (v0.8.0)

• add_memory: Stores a memory from text content or structured message arrays.

  • Inputs: content (string) or messages (array of role/content objects), userId (string), runId / sessionId (string), agentId (string), appId (string), metadata (object), infer (boolean), customInstructions (string), waitForCompletion (boolean, default: true), timeoutMs (number, default: 15000)

  • Behavior: Cloud V3 additions are asynchronous. By default, this tool polls the background queue until completed. Pass waitForCompletion: false to get the eventId immediately.

• search_memories: Searches memories using semantic and BM25 hybrid filters.

  • Inputs: query (string), userId (string), runId / sessionId (string), agentId (string), appId (string), filters (object), threshold (number), topK (number), rerank (boolean), referenceDate (string)

  • Behavior: Automatically nests scope variables inside the V3 filters block to prevent API validation errors.

• search_memory: Backward-compatible alias for search_memories.

• list_memories: Paginated listing of memory records scoped by identifiers.

  • Inputs: userId (string), runId / sessionId (string), agentId (string), appId (string), filters (object), page (number), pageSize (number)

• get_memory: Retrieves a single memory record by its ID.

  • Inputs: memoryId (string)

• update_memory: Modifies the text or metadata of an existing memory.

  • Inputs: memoryId (string), text (string), metadata (object)

• delete_memory: Deletes a specific memory record by ID.

  • Inputs: memoryId (string)

• get_memory_history: Retrieves the audit trail of memory revisions (cloud only).

  • Inputs: memoryId (string)

• get_memory_capabilities: Exposes the feature matrix and support flags of the active backend storage mode.

  • Inputs: None

• batch_update_memories: Performs bulk updates of text contents for multiple memories (cloud only).

  • Inputs: updates (array of { memoryId: string, text: string } objects)

• batch_delete_memories: Performs bulk deletions of multiple memories.

  • Inputs: memoryIds (array of strings), confirm (boolean, must be true to execute)

• rate_memory: Submits quality feedback evaluation for a memory record (cloud only).

  • Inputs: memoryId (string), feedback (string: positive, negative, very_negative), reason (string, optional)

• get_memory_event: Manually retrieves details of a specific background event job (cloud only).

  • Inputs: eventId (string)

• list_memory_events: Lists history logs of background memory processing events (cloud only).

  • Inputs: page (number), pageSize (number)

• create_memory_export: Initiates an asynchronous memory export query job (cloud only).

  • Inputs: schema (object), filters (object, optional), exportInstructions (string, optional)

• get_memory_export: Retrieves status and download metadata of a memory export job (cloud only).

  • Inputs: exportId (string)

Related MCP server: mindcore-memory-mcp

Prerequisites 🔑

This server supports three storage modes:

1. Cloud Storage Mode ☁️ (Recommended for production)

   • Requires a Mem0 API key (provided as MEM0_API_KEY environment variable)

   • Memories are persistently stored on Mem0's cloud servers

   • No local database needed

   • Full feature support with advanced filtering and search

2. Supabase Storage Mode 🗄️ (Recommended for self-hosting)

   • Requires Supabase credentials (SUPABASE_URL and SUPABASE_KEY environment variables)

   • Requires OpenAI API key (OPENAI_API_KEY environment variable) for embeddings

   • Memories are persistently stored in your Supabase database

   • Free tier available, self-hostable option

   • Requires initial database setup (SQL migrations provided below)

3. Local Storage Mode 💾 (Development/testing only)

   • Requires an OpenAI API key (provided as OPENAI_API_KEY environment variable)

   • Memories are stored in an in-memory vector database (non-persistent by default)

   • Data is lost when the server restarts unless configured for persistent storage

Installation & Configuration ⚙️

You can run this server in three main ways:

Installing via Smithery

To install Mem0 Memory Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @pinkpixel-dev/mem0-mcp-server --client claude

1. Global Installation (Recommended for frequent use)

Install the package globally and use the mem0-mcp command:

npm install -g @pinkpixel/mem0-mcp

After global installation, you can run the server directly:

mem0-mcp

Configure your MCP client to use the global command:

Cloud Storage Configuration (Global Install)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "mem0-mcp",
      "args": [],
      "env": {
        "MEM0_API_KEY": "YOUR_MEM0_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123",
        "DEFAULT_AGENT_ID": "your-agent-id",
        "DEFAULT_APP_ID": "your-app-id"
      }
    }
  }
}

Supabase Storage Configuration (Global Install)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "mem0-mcp",
      "args": [],
      "env": {
        "SUPABASE_URL": "YOUR_SUPABASE_PROJECT_URL",
        "SUPABASE_KEY": "YOUR_SUPABASE_ANON_KEY",
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123",
        "DEFAULT_AGENT_ID": "your-agent-id",
        "DEFAULT_APP_ID": "your-app-id"
      }
    }
  }
}

Local Storage Configuration (Global Install)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "mem0-mcp",
      "args": [],
      "env": {
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123"
      }
    }
  }
}

2. Using npx (Recommended for occasional use)

Configure your MCP client (e.g., Claude Desktop, Cursor, Cline, Roo Code, etc.) to run the server using npx:

Cloud Storage Configuration (npx)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@pinkpixel/mem0-mcp"
      ],
      "env": {
        "MEM0_API_KEY": "YOUR_MEM0_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123",
        "DEFAULT_AGENT_ID": "your-agent-id",
        "DEFAULT_APP_ID": "your-app-id"
      }
    }
  }
}

Supabase Storage Configuration (npx)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@pinkpixel/mem0-mcp"
      ],
      "env": {
        "SUPABASE_URL": "YOUR_SUPABASE_PROJECT_URL",
        "SUPABASE_KEY": "YOUR_SUPABASE_ANON_KEY",
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123",
        "DEFAULT_AGENT_ID": "your-agent-id",
        "DEFAULT_APP_ID": "your-app-id"
      }
    }
  }
}

Local Storage Configuration (npx)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@pinkpixel/mem0-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123"
      }
    }
  }
}

3. Running from Cloned Repository

Note: This method requires you to git clone the repository first.

Clone the repository, install dependencies, and build the server:

git clone https://github.com/pinkpixel-dev/mem0-mcp
cd mem0-mcp
npm install
npm run build

Then, configure your MCP client to run the built script directly using node:

Cloud Storage Configuration (Cloned Repository)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/mem0-mcp/build/index.js"
      ],
      "env": {
        "MEM0_API_KEY": "YOUR_MEM0_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123",
        "DEFAULT_AGENT_ID": "your-agent-id",
        "DEFAULT_APP_ID": "your-app-id"
      }
    }
  }
}

Supabase Storage Configuration (Cloned Repository)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/mem0-mcp/build/index.js"
      ],
      "env": {
        "SUPABASE_URL": "YOUR_SUPABASE_PROJECT_URL",
        "SUPABASE_KEY": "YOUR_SUPABASE_ANON_KEY",
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123",
        "DEFAULT_AGENT_ID": "your-agent-id",
        "DEFAULT_APP_ID": "your-app-id"
      }
    }
  }
}

Local Storage Configuration (Cloned Repository)

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/mem0-mcp/build/index.js"
      ],
      "env": {
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123"
      },
      "disabled": false,
      "alwaysAllow": [
        "add_memory",
        "search_memory",
        "delete_memory"
      ]
    }
  }
}

Important Notes:

1. Replace /absolute/path/to/mem0-mcp/ with the actual absolute path to your cloned repository

2. Use the build/index.js file, not the src/index.ts file

3. The MCP server requires clean stdout for protocol communication - any libraries or code that writes to stdout may interfere with the protocol

Supabase Setup 🗄️

If you choose to use Supabase storage mode, you'll need to set up your Supabase database with the required table.

1. Create a Supabase Project

1. Go to supabase.com and create a new project

2. Note your project URL and anon key from the project settings

2. Run SQL Migrations

Run these SQL commands in your Supabase SQL Editor:

-- Enable the vector extension
create extension if not exists vector;

-- Create the memories table
create table if not exists memories (
  id text primary key,
  embedding vector(1536),
  metadata jsonb,
  created_at timestamp with time zone default timezone('utc', now()),
  updated_at timestamp with time zone default timezone('utc', now())
);

-- Create the vector similarity search function
create or replace function match_vectors(
  query_embedding vector(1536),
  match_count int,
  filter jsonb default '{}'::jsonb
)
returns table (
  id text,
  similarity float,
  metadata jsonb
)
language plpgsql
as $$
begin
  return query
  select
    t.id::text,
    1 - (t.embedding <=> query_embedding) as similarity,
    t.metadata
  from memories t
  where case
    when filter::text = '{}'::text then true
    else t.metadata @> filter
  end
  order by t.embedding <=> query_embedding
  limit match_count;
end;
$$;

-- Create the memory_history table for history tracking
create table if not exists memory_history (
  id text primary key,
  memory_id text not null,
  previous_value text,
  new_value text,
  action text not null,
  created_at timestamp with time zone default timezone('utc', now()),
  updated_at timestamp with time zone,
  is_deleted integer default 0
);

3. Set Environment Variables

Add these to your MCP configuration:

• SUPABASE_URL: Your Supabase project URL (e.g., https://your-project.supabase.co)

• SUPABASE_KEY: Your Supabase anon key

• OPENAI_API_KEY: Your OpenAI API key (for embeddings)

Benefits of Supabase Mode

✅ Persistent Storage - Data survives server restarts ✅ Free Tier Available - Generous free tier for development ✅ Self-Hostable - Can run your own Supabase instance ✅ Scalable - Grows with your needs ✅ SQL Access - Direct database access for advanced queries ✅ Real-time Features - Built-in real-time subscriptions

Parameter Configuration 🎯

Understanding Mem0 Parameters

The server uses four key parameters to organize and scope memories:

1. userId - Identifies the user (required)

2. agentId - Identifies the LLM/agent making the tool call (optional)

3. appId - Identifies the user's project/application - this controls project scope! (optional)

4. sessionId - Identifies the conversation session (maps to run_id in Mem0) (optional)

Environment Variable Fallbacks 🔄

The MCP server supports environment variable fallbacks for user identification and project settings:

• DEFAULT_USER_ID: Fallback user ID when not provided in tool calls

• DEFAULT_AGENT_ID: Fallback agent ID for identifying the LLM/agent

• DEFAULT_APP_ID: Fallback app ID for project scoping

Priority Order (Important!)

1. Tool Parameters (highest priority) - Values provided by the LLM in tool calls

2. Environment Variables (fallback) - Values from your MCP configuration

Example Behavior:

// Your MCP config
"env": {
  "DEFAULT_USER_ID": "john-doe",
  "DEFAULT_AGENT_ID": "my-assistant",
  "DEFAULT_APP_ID": "my-project"
}

If LLM provides parameters:

{
  "tool": "add_memory",
  "arguments": {
    "content": "Remember this",
    "userId": "session-123",        // ← Overrides DEFAULT_USER_ID
    "agentId": "different-agent",   // ← Overrides DEFAULT_AGENT_ID
    "appId": "special-project"      // ← Overrides DEFAULT_APP_ID
    // sessionId omitted           // ← No fallback, will be undefined
  }
}

Result: Uses session-123, different-agent, and special-project

If LLM omits parameters:

{
  "tool": "add_memory",
  "arguments": {
    "content": "Remember this"
    // All IDs omitted - uses environment variables
  }
}

Result: Uses john-doe, my-assistant, and my-project

Controlling LLM Behavior

To ensure your environment variables are used, instruct your LLM:

• "Use the default user ID configured in the environment"

• "Don't specify userId, agentId, or appId parameters"

• "Let the server use the configured defaults"

System Prompt Recommendation

For best results, include instructions in your system prompt like:

When creating memories, use:
- agentId: "my-assistant"
- appId: "my-project"
- sessionId: "current-conversation-id"

Example configuration using DEFAULT_USER_ID:

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@pinkpixel/mem0-mcp"
      ],
      "env": {
        "MEM0_API_KEY": "YOUR_MEM0_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123",
        "ORG_ID": "your-org-id",
        "PROJECT_ID": "your-project-id"
      }
    }
  }
}

Or when running directly with node:

git clone https://github.com/pinkpixel-dev/mem0-mcp
cd mem0-mcp
npm install
npm run build

{
  "mcpServers": {
    "mem0-mcp": {
      "command": "node",
      "args": [
        "path/to/mem0-mcp/build/index.js"
      ],
      "env": {
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
        "DEFAULT_USER_ID": "user123"
      }
    }
  }
}

Storage Mode Comparison 🔄

Cloud Storage (Mem0 API) ☁️

• Persistent by default - Your memories remain available across sessions and server restarts

• No local database required - All data is stored on Mem0's servers

• Higher retrieval quality - Uses Mem0's optimized search algorithms

• Additional fields - Supports agent_id and threshold parameters

• Fully managed - No setup or maintenance required

• Requires - A Mem0 API key

Supabase Storage 🗄️

• Persistent storage - Data is stored in your Supabase PostgreSQL database

• Free tier available - Generous free tier for development and small projects

• Self-hostable - Can run your own Supabase instance for complete control

• SQL access - Direct database access for advanced queries and analytics

• Scalable - Grows with your needs, from free tier to enterprise

• Vector search - Uses pgvector extension for efficient similarity search

• Real-time features - Built-in real-time subscriptions and webhooks

• Requires - Supabase project setup and OpenAI API key for embeddings

Local Storage (OpenAI API) 💾

• In-memory by default - Data is stored only in RAM and is not persistent long-term. While some caching may occur, you should not rely on this for permanent storage.

• Data loss risk - Memory data will be lost on server restart, system reboot, or if the process is terminated

• Recommended for - Development, testing, or temporary use only

• For persistent storage - Use the Cloud Storage or Supabase options if you need reliable long-term memory

• Uses OpenAI embeddings - For vector search functionality

• Self-contained - All data stays on your machine

• Requires - An OpenAI API key

Development 💻

Clone the repository and install dependencies:

git clone https://github.com/pinkpixel-dev/mem0-mcp
cd mem0-mcp
npm install

Build the server:

npm run build

For development with auto-rebuild on file changes:

npm run watch

Debugging 🐞

Since MCP servers communicate over stdio, debugging can be challenging. Here are some approaches:

1. Use the MCP Inspector: This tool can monitor the MCP protocol communication:

npm run inspector

2. Console Logging: When adding console logs, always use console.error() instead of console.log() to avoid interfering with the MCP protocol

3. Environment Files: Use a .env file for local development to simplify setting API keys and other configuration options

Technical Implementation Notes 🔧

1. Platform V3 Async Additions & Polling

Mem0 Cloud V3 addition is an asynchronous background task. When calling add_memory, the server submits the request to /v3/memories/add/ and receives an eventId.

• Synchronous Polling (Default): The server polls the event status endpoint (/v1/event/{id}/) every 500ms for up to timeoutMs (default 15000ms) until the status becomes SUCCEEDED or FAILED. Once resolved, it returns the final outcome.

• Asynchronous Execution: Pass "waitForCompletion": false to bypass polling. The server will immediately return the eventId and a PENDING status.

2. Nested V3 Filter Normalization

The Mem0 Cloud V3 search and list endpoints reject top-level scope IDs (user_id, agent_id, app_id, run_id) and return an HTTP 400 error. V3 requires these fields inside the nested filters object. To prevent breaking client configurations, this server automatically normalizes top-level scope variables (userId, agentId, appId, runId/sessionId) and merges them into the nested filters object under the hood before sending the API request.

3. Capability Gating

Different backends support different feature sets. Call get_memory_capabilities to get a structured capability matrix of the active backend.

• Cloud Mode: Fully supports all features (apiVersion: "v3", async events, listing, audit histories, logical queries).

• Supabase / Local Modes: Standard V1 vector interfaces. Unsupported cloud-specific tools (like get_memory_history or list_memories) will fail gracefully with clear feature-unavailable messages.

4. Logging & Protocol Stability

MCP servers communicate using JSON-RPC over stdout. Any unexpected library logs printed to stdout will corrupt the protocol channel and cause clients to crash. This server overrides the default console output methods (such as console.log) to redirect/mute standard logging, ensuring clean stdio communication.

Made with 💖 by Pink Pixel