Unabyss

Unabyss is a universal context layer that ingests data from hundreds of apps, segments it across personal, professional, and confidential axes, and exposes it via the Model Context Protocol (MCP) to any AI agent or LLM. It solves the problem of fragmented, outdated context by continuously syncing sources like Slack, Notion, Gmail, GitHub, and Linear, so your AI always has up-to-date information. Built for builders, vibe coders, and knowledge workers who use multiple AI tools—Cursor, Claude Code, ChatGPT, Perplexity—Unabyss ensures that every agent sees the same current picture of your projects, meetings, and documents. It works by connecting your data sources once, generating an MCP token, and installing it into your agents with a single command. What makes Unabyss different is its three-layer context engine: segmentation (tagging every item by topic, confidence, sensitivity, and source), compression (extracting only relevant lines to reduce token usage by up to 10x), and a permission layer with four toggles (no restriction, exclude private, exclude confidential, exclude an entire source app) applied at retrieval time. The result is cheaper, faster, and safer AI interactions. Recent updates include per-memory cost limits to cap large file imports, more reliable syncs, integration availability fixes, and a new FAQ page. Unabyss is designed to complement—not replace—existing AI tools, making it ideal for multi-agent setups where context consistency is critical.