Memphora Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Memphora Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<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>
This MCP server connects your AI assistant to Memphora, giving it the ability to:
# Using pip
pip install memphora-mcp
# Or using uvx (recommended for Claude Desktop)
uvx memphora-mcpAdd 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"
}
}
}
}Close and reopen Claude Desktop. You should see the Memphora tools available!
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."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."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..."| 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 |
| Environment Variable | Description | Default |
|---|---|---|
MEMPHORA_API_KEY | Your Memphora API key | Required |
MEMPHORA_USER_ID | Unique identifier for your memories | mcp_default_user |
Add to your Cursor settings:
{
"mcp": {
"servers": {
"memphora": {
"command": "uvx",
"args": ["memphora-mcp"],
"env": {
"MEMPHORA_API_KEY": "your_api_key_here"
}
}
}
}
}Add to your Windsurf MCP configuration:
{
"mcpServers": {
"memphora": {
"command": "python",
"args": ["-m", "memphora_mcp"],
"env": {
"MEMPHORA_API_KEY": "your_api_key_here"
}
}
}
}# 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_mcppytest tests/MIT License - see LICENSE for details.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.