Memphora

Memphora MCP Server

Add persistent memory to Claude, Cursor, Windsurf, and other AI assistants using the Model Context Protocol (MCP).

What is this?

This MCP server connects your AI assistant to Memphora, giving it the ability to:

• Remember information across conversations
• Search your personal knowledge base
• Extract insights from conversations automatically
• Recall your preferences, facts, and context

Quick Start

1. Install

# Using pip
pip install memphora-mcp

# Or using uvx (recommended for Claude Desktop)
uvx memphora-mcp

2. Get Your API Key

1. Go to memphora.ai/dashboard
2. Create an account or sign in
3. Copy your API key from the dashboard

3. Configure Claude Desktop

Add to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "memphora": {
      "command": "uvx",
      "args": ["memphora-mcp"],
      "env": {
        "MEMPHORA_API_KEY": "your_api_key_here",
        "MEMPHORA_USER_ID": "your_unique_user_id"
      }
    }
  }
}

4. Restart Claude Desktop

Close and reopen Claude Desktop. You should see the Memphora tools available!

Usage Examples

Storing Memories

Just tell Claude something about yourself:

You: "I work at Google as a software engineer"
Claude: [stores memory] "Got it! I'll remember that you work at Google as a software engineer."

You: "My favorite programming language is Python"
Claude: [stores memory] "Noted! I'll remember that Python is your favorite programming language."

Recalling Memories

Ask Claude about things you've told it before:

You: "Where do I work?"
Claude: [searches memories] "You work at Google as a software engineer."

You: "What programming languages do I like?"
Claude: [searches memories] "Your favorite programming language is Python."

Automatic Context

Claude will automatically search your memories when relevant:

You: "Can you help me with some code?"
Claude: [searches memories for context]
        "Sure! Since you prefer Python and work at Google, I'll write this in Python 
         following Google's style guide..."

Available Tools

Tool	Description
memphora_search	Search memories for relevant information
memphora_store	Store new information for future recall
memphora_extract_conversation	Extract memories from a conversation
memphora_list_memories	List all stored memories
memphora_delete	Delete a specific memory

Configuration Options

Environment Variable	Description	Default
MEMPHORA_API_KEY	Your Memphora API key	Required
MEMPHORA_USER_ID	Unique identifier for your memories	mcp_default_user

Using with Other MCP Clients

Cursor

Add to your Cursor settings:

{
  "mcp": {
    "servers": {
      "memphora": {
        "command": "uvx",
        "args": ["memphora-mcp"],
        "env": {
          "MEMPHORA_API_KEY": "your_api_key_here"
        }
      }
    }
  }
}

Windsurf

Add to your Windsurf MCP configuration:

{
  "mcpServers": {
    "memphora": {
      "command": "python",
      "args": ["-m", "memphora_mcp"],
      "env": {
        "MEMPHORA_API_KEY": "your_api_key_here"
      }
    }
  }
}

Development

Running Locally

# Clone the repo
git clone https://github.com/Memphora/memphora-mcp.git
cd memphora-mcp

# Install dependencies
pip install -e ".[dev]"

# Set your API key
export MEMPHORA_API_KEY="your_key"

# Run the server
python -m memphora_mcp

Testing

pytest tests/

Privacy & Security

• Your memories are stored securely in Memphora's cloud
• Each user has isolated memory storage
• API keys are stored locally on your machine
• All communication is encrypted via HTTPS

Support

• Documentation: memphora.ai/docs
• Issues: GitHub Issues
• Email: support@memphora.ai

License

MIT License - see LICENSE for details.