Use cases

Your agents finally know what you know

You wire up Claude, Cursor, Codex, or n8n - and every one starts from zero. Unabyss gives them one shared context, so what one knows, they all know.

Connect your stack - free

Write a message...

Claude is AI and can make mistakes. Please double-check responses.

Infrastructure decisions follow you into Claude

You worked through GCP vs AWS in Cursor this morning. Open Claude and it already knows why you chose GCP, what you rejected, and whether current costs mean it's time to reconsider - without re-pasting the thread.

The pain

The problem builders feel every day

You switch tools all day

Claude this morning, Cursor now, an automation after that. Every switch means re-explaining the project, the stack, the decisions you just made.

Every agent starts from zero

Reopen the repo and your agent has amnesia - conventions, context, where you left off, all gone. You set the scene again before it's useful.

Your stack doesn't share

A coding agent here, an automation there, a chat assistant for everything else - none of them share what they know. You become the integration.

Moment to moment

What changes, moment to moment

Billing deploy safety

Plan, Build, / for skills, @ for context

Auto

Pick up the billing migration where you left off

You reopen your app after a week away. Instead of re-reading PR #212 and digging through Linear, Unabyss surfaces the legacy cohort risk, in-flight tickets, and the safe deploy path.

Write a message...

Claude is AI and can make mistakes. Please double-check responses.

Spin up a repo the way you always do

Your agent or automation used to follow a stale template. Unabyss pulls how you structure projects from past repos - pnpm, Biome, Drizzle, tag-only deploys - so every scaffold matches what you actually ship.

Replace them all with one MCP connection

Replace them all with one MCP connection that stays current automatically. Your context updates itself from GitHub, Linear, Notion - it never goes stale, and you never re-upload it to another tool again.

Connect your first source

How you work

Built for how you actually work

Connect once - every authorized agent, tool, and automation pulls fresh context on demand.
Works across MCP clients: Claude Desktop & Code, Cursor, Codex - plus Make, n8n, and Zapier.
Stays current automatically from your real sources (GitHub, Linear, Notion, Gmail, Calendar).
Pulls only the lines that answer the question - so you save on tokens instead of dumping raw context.
Granular, per-app and per-file permissions - you decide what each tool sees.
Export everything as Markdown anytime. No lock-in.

Trust

Your context. Your rules.

You own it.

Unabyss is an independent context layer - not memory trapped inside one vendor. Plug in any agent, connect any source, and take your context anywhere.

Granular permissions.

Per-app, per-file - share what's relevant, withhold the rest.

Never sold.

Never used to train models. Your context stays yours.

Compare

Comparing something else?

Weighing Unabyss against another way of giving AI context?

Unabyss vs. built-in AI memory

Built-in memory is useful, but it's trapped in one tool - what ChatGPT learns stays in ChatGPT, and Claude's memory can't help Cursor. Unabyss is a context layer you own, served to every AI tool over MCP.

Read the full comparison

Unabyss vs. context files

Unabyss vs. building your own context system

AI memory vs. AI context

One context for every agent

Connect a source and your agents answer with context they never had before.

Under a minute to set up Connect your stack - free