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Home/Servers/Memphora

Memphora

by io.github.Memphora

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

Power your agent

Add this server

The publisher's own command. Not a PlugMCP endpoint.

Local command
uvx memphora-mcp==0.1.3
Credentials from the publisher
  • MEMPHORA_API_KEY β€” Your Memphora API key from memphora.ai/dashboard
  • MEMPHORA_USER_ID β€” Unique identifier for your memories
Provider
Claude Code
MEMPHORA_API_KEY=<secret> MEMPHORA_USER_ID=<value> claude mcp add io.github.memphora-memphora -- uvx memphora-mcp==0.1.3

Run in a terminal.

Claude Desktop
{
  "mcpServers": {
    "io.github.memphora-memphora": {
      "command": "uvx",
      "args": [
        "memphora-mcp==0.1.3"
      ],
      "env": {
        "MEMPHORA_API_KEY": "<secret>",
        "MEMPHORA_USER_ID": "<value>"
      }
    }
  }
}

claude_desktop_config.json

Step-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

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

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

  • Documentation: memphora.ai/docs
  • Issues: GitHub Issues
  • Email: [email protected]

License

MIT License - see LICENSE for details.

How do I install Memphora?
Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.
Does Memphora need an API key?
The publisher lists these environment variables: MEMPHORA_API_KEY, MEMPHORA_USER_ID.
What transport does Memphora use?
Memphora runs locally over stdio.
When was Memphora last checked?
Last checked 2026-10-16. Add persistent memory to AI assistants. Store and recall info across conversations.

No tool list yet. Remote servers get one after the first health check.

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