ghostmail is a lightweight, modular email monitoring framework that extracts actionable context from your inbox and injects it directly into LLMs. It transforms structured email signals into agent-ready memory blocks — enabling smarter, more responsive autonomous workflows.
Ghostmail combines cyberpunk aesthetics with powerful email processing to create AI-ready context blocks. The framework features:
- Structured email signal extraction
- LLM-compatible memory block generation
- Cyberpunk-themed command interface
- Ghost animations and transitions
- Rich text formatting and colors
- 🤖 AI-Ready Context Blocks
- 🧠 LLM-Compatible Memory Format
- 👻 Cyberpunk Ghost Interface
- 🎨 Rich Text Formatting
- 🚀 Fast and Lightweight
The initial implementation focused on creating a cyberpunk-themed CLI interface with ghost animations. This served as a proof of concept for the visual and interactive aspects of the framework. As the project evolved, we refined the core functionality to focus on AI and autonomous agent integration, transforming email signals into structured context blocks that can be directly consumed by LLMs.
Ghostmail is currently only available through local development setup:
git clone https://github.com/yourusername/ghostmail.git
cd ghostmail
pip install -e .Run the tool using:
ghostmailrecruiters?- Extract and structure job opportunity signals into AI-ready context blocksstatements?- Process financial statements into structured data for agent analysispackages?- Transform delivery updates into actionable tracking events
gh0st!- Display the command matrix with ghost animationsp00ky!- Show a spooky ASCII art ghostb00!- Display a boo messagegl1tch!- Show a glitch effect
Ghostmail is built with:
click- For CLI implementationrich- For rich text and cyberpunk aesthetic
MIT License