Unabyss

About

Unabyss sits between your working tools and your AI tools. Instead of copying the same biography, company facts, docs, and preferences into every assistant, it turns that material into a structured context layer that Claude, Codex, Cursor, ChatGPT, and other clients can read on demand.

Why It Is Hot Now

It is hot right now because it launched on Product Hunt this week, hit #1 for the day, and tapped into a pain point many heavy AI users already feel: context is trapped inside one app, stale inside another, and missing everywhere else.

Key Features

• Connects many daily apps and keeps context refreshed instead of relying on one-time prompt stuffing.
• Serves context through MCP with granular filters for private, confidential, or source-level exclusions.
• Segments and compresses context so agents fetch only the relevant lines instead of dragging a whole vault into every prompt.

Real Use Cases

• Founders who bounce between Claude, Cursor, Codex, and ChatGPT but want the same company and personal context everywhere.
• Teams that need on-brand drafts, meeting prep, and investor summaries without repeating internal facts by hand.
• Operators who want a readable, user-owned source of truth instead of opaque memory hidden inside one AI vendor.

Community Pulse

The launch discussion was positive about the user-owned layered files and the cross-tool MCP setup. The sharper questions were about staleness, cache drift, and whether the extra retrieval hop is worth it when local rules or project files are already in place.

Limits and Risks

This kind of product only works if connectors stay healthy, permissions are configured carefully, and refresh logic catches real-world changes fast enough. MCP retrieval can also add latency compared with stuffing static rules into one local tool.

Alternatives

Nearby options include Claude Projects, hand-maintained markdown context packs, Mem0, Supermemory, Graphlit, and other memory layers that trade off freshness, ownership, and retrieval control differently.

FAQ

• Who should try Unabyss first? People using several AI tools every day who are tired of re-explaining their role, preferences, company, and active projects.
• What should you validate early? Connector freshness, permission boundaries, and whether MCP retrieval is faster and cheaper than your current prompt or rules workflow.