Personal Memory Gateway
A privacy-first memory layer for AI that securely bridges local knowledge with AI assistants through MCP tools, with intelligent redaction and local vector database.
README
🧠 Personal Memory Gateway (PMG)
The Privacy-First Memory Layer for AI.
Seamlessly bridge your local knowledge with any AI assistant through a secure, MCP-compatible gateway.
🚀 Quick Start
Get up and running in seconds with zero configuration:
npx @shubham-01-star/pmg init
✨ Overview
Personal Memory Gateway (PMG) is a local-first backend designed to store, manage, and serve your personal knowledge to AI models. It acts as a secure "VPN for your memory," ensuring that sensitive data is redacted and privacy is gated before any context is shared.
🛠️ Core Capabilities
- MCP Tool Integration: Seamlessly connects to Cursor, Claude Desktop, and other MCP clients via
query_personal_memoryandsave_memorytools. - Privacy-First Ingestion: Automatically watches local directories, chunks documents, and stores them in a local vector database (LanceDB).
- Intelligent Redaction: Applies a multi-stage pipeline to redact PII and sensitive information before retrieval.
- Archestra Integration: Optionally route responses through high-performance gateways like Archestra (supporting Gemini/OpenAI).
- Telemetry Dashboard: Monitor system health and manage your indexed data through a built-in web interface.
🏗️ Architecture
graph TD
A[Local Files] -->|Ingestion| B(Chunking & Embedding)
B -->|LanceDB| C[Vector Repository]
D[MCP Client] -->|Query| E[Privacy Pipeline]
E -->|Redaction| F[Consent Gate]
F -->|Context| G[AI Model]
C -->|Retrieval| E
📦 Installation
Global Install (Recommended)
npm i -g @shubham-01-star/pmg
pmg init
pmg
Local Development
git clone https://github.com/shubham-01-star/pmg.git
cd pmg
npm install
npm run build
npm run run
🔌 MCP Client Configuration
Add PMG to your mcpServers configuration:
{
"mcpServers": {
"pmg": {
"command": "npx",
"args": ["-y", "@shubham-01-star/pmg"],
"env": {
"INGEST_DIR": "/path/to/your/data",
"LANCE_DB_PATH": "/path/to/lancedb/storage"
}
}
}
}
⚙️ Environment Variables
| Variable | Description | Default |
|---|---|---|
INGEST_DIR |
Directory to watch for memory files | my_data |
ARCHESTRA_ENABLE |
Enable Archestra integration (0 or 1) |
0 |
EMBEDDING_PROVIDER |
Embedding model source (local, gemini, etc.) |
local |
DASHBOARD_PORT |
Port for the telemetry dashboard | 8787 |
PRIVACY_REDACT_PII |
Enable PII redaction pipeline | 1 |
📊 Dashboard
Once running, access the telemetry dashboard at: 👉 http://localhost:8787/dashboard
- Monitor: Real-time events and memory retrieval stats.
- Manage: Upload new documents or clear existing memories.
- Status: Visual health probes for all internal services.
🧪 Testing & Verification
PMG includes a comprehensive suite of smoke tests and backend validations.
# Run backend smoke suite
make test-backend
# Integrated flow test
node scripts/one-command-flow.mjs "topic" "path/to/sample.txt"
📜 License
Distributed under the MIT License. See LICENSE for more information.
<p align="center"> Built with ❤️ for the <b>2 Fast 2 MCP Hackathon</b> </p>
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