Lilith Emails
The Lilith Email System is a project that integrates a Gmail synchronization daemon and a semantic search proxy tool. It supports privacy - aware classification, PII desensitization, and multi - level embedding, and provides an email query tool for AI agents through the MCP server.
rating : 2 points
downloads : 6.0K
What is Lilith Email System?
Lilith Email System is an intelligent email management solution that securely synchronizes your Gmail emails to a local database, automatically categorizes email content, performs privacy protection processing, and conducts semantic analysis. The system provides secure email access capabilities for AI assistants through the Model Context Protocol (MCP), allowing you to search for and manage emails using natural language while protecting sensitive information.How to use Lilith Email System?
The usage is divided into three main stages: 1) Configure your Gmail account and synchronize emails to the local database; 2) Run the intelligent processing flow to categorize emails, protect privacy, and conduct semantic analysis; 3) Start the MCP server to allow AI assistants to securely access and process your emails. The entire process focuses on privacy protection, and sensitive information will be automatically identified and desensitized.Use Cases
Suitable for users who need to process a large number of emails frequently, especially: professionals who need to quickly find historical emails; users who are concerned about privacy protection and do not want to send email content to third-party AI services; teams and individuals who want to interact with the email system using natural language to improve work efficiency.Main Features
Secure Gmail Synchronization
Incrementally synchronize Gmail emails to a local PostgreSQL database through OAuth secure authentication, supporting complete email metadata and attachment information.
Intelligent Privacy Protection
Automatically identify the privacy level of emails (public, personal, sensitive) and desensitize sensitive content to protect personal information security.
Semantic Search
Use embedding vector technology to support natural language semantic search, understanding the query intention rather than simple keyword matching.
MCP Protocol Integration
Provide a standardized email access interface for AI assistants through the Model Context Protocol, supporting multiple AI tools and platforms.
Real-time Updates
Support Gmail Pub/Sub push notifications. When emails change, synchronization and processing are automatically triggered to keep the data up-to-date.
Multi-language Support
Automatically detect the language of emails and use corresponding NLP processing models for different languages to ensure processing accuracy.
Advantages
Privacy-first: All processing is done locally, and sensitive information will not be leaked to third parties.
Intelligent classification: Automatically identify email types and privacy levels, reducing manual sorting work.
Natural interaction: Through the MCP protocol, you can communicate with the email system using natural language.
Offline access: Email data is stored locally, allowing you to search and view emails even without an internet connection.
Scalability: Modular design, supporting custom processing flows and integrations.
Limitations
Complex initial configuration: Requires setting up a database, Gmail API, and multiple microservices.
High resource requirements: Needs to run PostgreSQL and multiple AI model services.
Only supports Gmail: Currently mainly targeted at the Gmail email system.
Technical requirements: Requires certain technical knowledge for deployment and maintenance.
Local storage: Requires sufficient disk space to store emails and vector data.
How to Use
Environment Preparation
Ensure that Python and the PostgreSQL database are installed, and clone the lilith-compose project. Create an.env file to configure the database connection and other service URLs.
Database Initialization
Run database migrations to create necessary tables and indexes.
Add Gmail Account
Download the OAuth client secret from the Google Cloud Console and add it to the system.
First Email Synchronization
Download all historical emails to the local database.
Intelligent Processing
Perform categorization, privacy protection, and semantic analysis on emails.
Start MCP Server
Start the MCP server to allow AI assistants to access the processed email data.
Usage Examples
Find Meeting Records
You need to find emails about the project review meeting last week, but you can't remember the specific title and sender.
Summarize Customer Communication
You need to quickly understand the recent communication situation and to - do items with a certain customer.
Find Technical Documents
You need to find an email sent by a colleague that contains an API document attachment.
Privacy - Protected Search
Search for emails that contain personal sensitive information, but hope the system will automatically desensitize and display them.
Frequently Asked Questions
Is my email data secure?
Which email services are supported?
How much storage space is required?
How to handle new emails?
Can I manage multiple Gmail accounts simultaneously?
How can an AI assistant access my emails?
What is the processing speed like?
How to back up data?
Related Resources
GitHub Repository
Project source code and latest updates
Model Context Protocol Documentation
Official specification of the MCP protocol
Google Cloud Console
Obtain Gmail API credentials
PostgreSQL Documentation
Database configuration and management guide
Deployment Video Tutorial
Step - by - step deployment and configuration demonstration
Problem Feedback
Report problems and feature requests

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
25.1K
4.3 points

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
20.8K
4.5 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
73.0K
4.3 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
35.2K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
65.9K
4.5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
33.2K
5 points

Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
21.3K
4.5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
98.0K
4.7 points




