MedMemory

MedMemory

This MCP is capable of analyzing medical documents and prescriptions and giving patient all the medical info it needs and answering their questions

Category
Visit Server

README

MedMemory MCP

PyPI version Python 3.12+ License: MIT Downloads Glama

Privacy-first personal health record MCP server — store medical documents locally with AES-256 encryption and query with Claude.

MedMemory lets you ingest prescriptions, lab reports, and discharge summaries into an encrypted local database, then ask Claude questions about your health history in natural language. Your data never leaves your machine.

Demo

MedMemory Demo

Features

  • 8 MCP tools — medications, lab trends, drug interactions, vaccination status, visit history, allergies, health summary, document ingestion
  • Privacy-first — AES-256 encrypted SQLite database, nothing sent to cloud storage
  • Gemini Vision — reads handwritten prescriptions and scanned PDFs natively
  • Drug interaction checker — real-time OpenFDA API lookup against your current medication list
  • WHO vaccination schedule — cross-references your records and flags overdue vaccines
  • Companion web UI — 6-page Next.js dashboard at medmemory-ui.vercel.app
  • Works with Claude Desktop and Cursor

Quick Start

pip install medmemory-mcp
medmemory-setup

Then add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "medmemory": {
      "command": "medmemory-server"
    }
  }
}

Restart Claude Desktop. MedMemory is ready.

Try the Hosted Demo

No installation needed — connect to the Railway demo server with synthetic patient data:

{
  "mcpServers": {
    "medmemory-demo": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://web-production-ba446.up.railway.app/sse"]
    }
  }
}

Tools

Tool Description Example prompt
ingest_health_document Parse any medical PDF or image into the DB "Ingest this prescription: /path/to/rx.pdf"
get_current_medications Return active medication list "What medications am I on?"
get_lab_trend Historical readings for any lab marker "Show me my HbA1c trend"
get_visit_history Doctor visits with specialty filter "What did my cardiologist say?"
get_vaccination_status Cross-reference WHO schedule, flag gaps "Am I up to date on vaccines?"
check_drug_interaction OpenFDA lookup against your med list "Is Ibuprofen safe with my medications?"
get_allergies Return recorded allergies "What allergies do I have on record?"
generate_health_summary Printable one-pager for new doctors "Generate my health summary"

Privacy Architecture

What Where it goes
Your health records Local encrypted SQLite only
Encryption key Your machine only, never transmitted
Document text during ingestion Gemini API (transient, not stored)
Drug name during interaction check OpenFDA API only
Tool call results Anthropic (same as any Claude conversation)

Verify the encryption yourself:

xxd ~/medmemory.db | head -3
# Should show random bytes — not "SQLite format 3"

See PRIVACY.md for full details.

Web UI

Live at medmemory-ui.vercel.app

6 pages: Dashboard · Upload · Medications · Lab Results · Timeline · Health Summary

Development

# Clone and install
git clone https://github.com/priyanshugoel24/medmemory-mcp
cd medmemory-mcp
uv sync

# Set up environment
cp .env.example .env
# Add GEMINI_API_KEY, OPENFDA_API_KEY, MEDMEMORY_DB_KEY

# Seed test data
uv run seed_data.py

# Run MCP server in dev mode
uv run mcp dev medmemory/server.py

# Run FastAPI bridge
uv run uvicorn medmemory.api:app --reload --port 8000

# Run Next.js UI
cd ui && npm run dev

Project Structure

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured