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MineContext

MineContext is an open-source proactive context-aware AI partner designed to bring clarity and efficiency to your work, study, and creation. It captures and understands your digital world context via screenshots and content comprehension (with future support for multi-modal sources like documents, images, videos, code), and proactively delivers high-quality information such as insights, daily/weekly summaries, to-do lists, and activity records using a context engineering framework.

Introduction

MineContext: An Open-Source Proactive Context-Aware AI Partner

Overview

MineContext is a cutting-edge, open-source desktop application that acts as your intelligent AI companion, transforming chaotic digital workflows into structured, actionable insights. Developed by Volcengine (a ByteDance subsidiary), it leverages advanced context capture and processing to 'see' and comprehend your screen activities, documents, and interactions in real-time. Unlike passive AI tools, MineContext is proactive—it automatically generates summaries, to-dos, and recommendations without requiring constant user input, making it ideal for knowledge workers, content creators, and lifelong learners.

The core philosophy behind MineContext draws inspiration from Minecraft, symbolizing the 'mining' of context from scattered digital 'blocks' to build a personalized 'world' of productivity. Launched in late 2025, it has quickly gained traction with over 4,000 GitHub stars, reflecting its innovative approach to context engineering.

Key Features

MineContext excels in four primary areas:

  1. Effortless Collection: It seamlessly gathers massive amounts of contextual data through periodic screenshots (configurable intervals), document monitoring, and future integrations like file uploads and browser extensions. Storage is optimized for local devices, preventing mental overload while handling multimodal inputs (text, images, code, etc.).

  2. Proactive Delivery: In everyday use, it pushes curated content to your dashboard, including daily/weekly summaries of activities, extracted to-do lists, productivity tips, and insightful observations. This eliminates the need to manually query the AI—insights arrive when you need them.

  3. Intelligent Resurfacing: During creative or analytical tasks, MineContext intelligently retrieves and surfaces relevant past contexts, ensuring inspiration without information overload. For example, while writing, it might recall similar projects or resources from your history.

  4. Context Engineering Architecture: At its heart is a robust framework managing the full lifecycle of data: capture, processing (chunking, entity extraction, deduplication), storage (SQLite and vector databases like ChromaDB), retrieval, and consumption. It supports six types of intelligent outputs and is extensible for new data sources.

Technical Architecture

The project is split into frontend and backend components for cross-platform compatibility (Mac, Windows, Linux planned).

Frontend

Built with Electron, React, TypeScript, Vite, and Tailwind CSS, the UI is modern and responsive. The architecture separates main process (window management, IPC), preload scripts (secure API exposure), and renderer (React-based interface with state management via Jotai/Redux). Development involves pnpm for dependencies and electron-builder for packaging.

Backend

Powered by FastAPI (Python), it includes layers for server (RESTful APIs, WebSockets), managers (capture, processing, consumption), context modules (screenshot capture, multimodal processing), storage (multi-backend support), LLM integration (OpenAI-compatible providers like Doubao, OpenAI, local models via LMStudio), and tools/monitoring. Configuration is YAML-based, with prompts for English/Chinese.

Installation is straightforward: Use uv for dependency management, then run opencontext start. It supports local-first data storage at ~/Library/Application Support/MineContext/Data and debugging via http://localhost:1733.

Privacy and Integration

Privacy is paramount: All data stays local by default, with no cloud dependency. It integrates with LLM providers via API keys (recommended: Doubao for cost/performance balance, with models like Doubao-Seed-1.6-flash for vision-language tasks and Doubao-embedding-large for embeddings). Local models ensure zero data leakage.

Future expansions include P0-P5 context sources: from PC screenshots and links (current) to WeChat chats, RSS feeds, and even wearable data sync.

Target Users and Comparisons

Tailored for researchers, writers, students, and project managers facing information overload. Compared to ChatGPT Pulse, it's local-first, open-source, and more comprehensive in context capture without subscription costs. Versus Dayflow, it offers richer AI-driven insights and interactive Q&A.

Community and Contribution

Join via WeChat, Discord, or GitHub. Contributions welcome for frontend/backend, with detailed guides. Licensed under Apache 2.0.

MineContext redefines AI assistance by making your digital life contextually intelligent and proactive, fostering creativity in an increasingly complex world.

Information

  • Websitegithub.com
  • AuthorsVolcengine
  • Published date2025/10/10