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Memphora

Official registry AI and agents

Add persistent memory to AI assistants. Store and recall info across conversations.

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

PYPI package memphora-mcp
Claude Code 
claude mcp add memphora -e 'MEMPHORA_API_KEY=<your memphora_api_key>' -e 'MEMPHORA_USER_ID=<MEMPHORA_USER_ID>' -- uvx memphora-mcp==0.1.3
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "memphora": {
            "command": "uvx",
            "args": [
                "memphora-mcp==0.1.3"
            ],
            "env": {
                "MEMPHORA_API_KEY": "<your memphora_api_key>",
                "MEMPHORA_USER_ID": "<MEMPHORA_USER_ID>"
            }
        }
    }
}

Environment variables

  • MEMPHORA_API_KEY required secret Your Memphora API key from memphora.ai/dashboard
  • MEMPHORA_USER_ID Unique identifier for your memories

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Memphora MCP Server
  2. What is this?
  3. Quick Start
  4. Usage Examples
  5. Available Tools
  6. Configuration Options
  7. Using with Other MCP Clients
  8. Development
  9. Privacy & Security
  10. Support
  11. License

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

ToolDescription
memphora_searchSearch memories for relevant information
memphora_storeStore new information for future recall
memphora_extract_conversationExtract memories from a conversation
memphora_list_memoriesList all stored memories
memphora_deleteDelete a specific memory

Configuration Options

Environment VariableDescriptionDefault
MEMPHORA_API_KEYYour Memphora API keyRequired
MEMPHORA_USER_IDUnique identifier for your memoriesmcp_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

License

MIT License - see LICENSE for details.

Frequently asked questions

What is Memphora?

Add persistent memory to AI assistants. Store and recall info across conversations.

How do I install Memphora?

It runs on your machine. In Claude Code: claude mcp add memphora -e 'MEMPHORA_API_KEY=<your memphora_api_key>' -e 'MEMPHORA_USER_ID=<MEMPHORA_USER_ID>' -- uvx memphora-mcp==0.1.3. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Memphora need an API key?

Yes. It expects MEMPHORA_API_KEY, which you set in its configuration.

Is Memphora open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains Memphora?

It is published by Memphora. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.