<p align="center">
<img src="logo.png" alt="Memphora Logo" width="120" height="120">
</p>
<h1 align="center">Memphora MCP Server</h1>
<!-- mcp-name: io.github.Memphora/memphora -->
<p align="center">
<strong>Add persistent memory to Claude, Cursor, Windsurf, and other AI assistants using the Model Context Protocol (MCP).</strong>
</p>
<p align="center">
<a href="https://pypi.org/project/memphora-mcp/"><img src="https://img.shields.io/pypi/v/memphora-mcp.svg" alt="PyPI"></a>
<a href="https://github.com/Memphora/memphora-mcp/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="License"></a>
<a href="https://memphora.ai"><img src="https://img.shields.io/badge/website-memphora.ai-orange.svg" alt="Website"></a>
</p>
## What is this?
This MCP server connects your AI assistant to [Memphora](https://memphora.ai), 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
```bash
# 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](https://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`
```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:
```json
{
"mcp": {
"servers": {
"memphora": {
"command": "uvx",
"args": ["memphora-mcp"],
"env": {
"MEMPHORA_API_KEY": "your_api_key_here"
}
}
}
}
}
```
### Windsurf
Add to your Windsurf MCP configuration:
```json
{
"mcpServers": {
"memphora": {
"command": "python",
"args": ["-m", "memphora_mcp"],
"env": {
"MEMPHORA_API_KEY": "your_api_key_here"
}
}
}
}
```
## Development
### Running Locally
```bash
# 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
```bash
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](https://memphora.ai/docs)
- Issues: [GitHub Issues](https://github.com/Memphora/memphora-mcp/issues)
- Email: support@memphora.ai
## License
MIT License - see [LICENSE](LICENSE) for details.
