Unabyss

Unabyss is a universal context layer for AI tools that keeps connected app data current and available through MCP for scoped retrieval.

AI Developer Tools AI Agents Directory AI Knowledge Management

Visit Website

Overview

Unabyss is a universal context layer for AI tools. It connects to the apps and agents you already use, keeps that data current, and makes it available through MCP so LLMs can retrieve relevant context on demand.

The product is built around segmentation and controlled retrieval. Rather than sending an entire history into a model, Unabyss tags incoming material, filters it by scope, and surfaces only the context that matches the current question or workflow.

Core features

Always-current context sync

Connect sources once and bring in data from many apps, then keep that context current automatically as the underlying tools change.

MCP access for agents

Route context through MCP so supported agents and LLMs can read the same context layer on demand, rather than starting from scratch in each tool.

Context segmentation

Tag incoming context across topic, confidence, sensitivity, source app, and personal versus professional dimensions so retrieval can target a narrower slice.

Targeted retrieval

Retrieve only the lines that answer a question and surface less prompt material than standard chunk-based RAG, which the site says can cut token usage by up to 10×.

Permission controls

Apply retrieval-time scopes such as private, confidential, or whole-app exclusions so blocked context never reaches the model.

Context-aware skills library

Use the Skills Library to run Claude skills against live Unabyss context, with one-click MCP setup instead of downloading each skill separately.

Common use cases

Shared context across agents
Keep Claude, Cursor, Codex, or other supported agents working from the same live source of truth instead of separate, stale snippets.
Drafting from connected work history
Pull relevant notes, messages, and files from connected apps when drafting posts, updates, offers, or summaries without manually assembling background material.
Scoped context for sensitive work
Limit what an assistant can see by excluding private items, confidential work, or entire source apps before retrieval happens.
Context-aware Claude workflows
Use the Skills Library to run Claude skills against current company, personal, or brand context so outputs reflect the latest state.
Cross-tool operational context
Sync sources like GitHub, Linear, Gmail, Slack, Notion, and calendar tools so day-to-day planning and follow-up happen from one place.

Pros and Cons

Pros

Connects many everyday work apps and AI clients into one context layer.
Supports MCP, which lets compatible agents and LLMs read context without manual copying.
Includes retrieval-time permission scopes that can exclude private, confidential, or entire app sources.
Uses segmentation and targeted retrieval to reduce how much text gets passed into the model.
Adds a Claude skills library that runs on real Unabyss context instead of blank templates.

Cons

The public pricing page returns a 404, so pricing details and plan structure are not verified from the source.
The source shows broad integration coverage, but some integrations are marked as coming soon or were added recently, so availability may vary by connector.

FAQ

How does Unabyss work with AI agents?

Unabyss connects sources once, then makes that context available through MCP so supported agents and LLMs can read it on demand. The site describes a first-connect MCP setup for LLM clients and a context layer that stays up to date as your connected apps change.

Can I control what context gets surfaced?

The site describes four retrieval scopes: no restriction, exclude private information, exclude company confidential, or exclude an entire source app. It also says filters are applied at retrieval time so blocked context does not reach the model.

Which tools and apps does Unabyss connect to?

The integrations page lists MCP clients such as Claude, Cursor, Claude Code, OpenClaw, ChatGPT, Hermes, VS Code, OpenCode, Codex, and Perplexity, plus app connections like Notion, Slack, Gmail, Google Drive, Google Calendar, GitHub, GitLab, Linear, Jira, HubSpot, Pipedrive, Todoist, ClickUp, Monday.com, and more.

What does pricing look like?

The pricing page is not available, but the home page says you get $25 in free credits on signup, no card is required to start, and then you pay as you go after credits run out.

Who is Unabyss for?

Unabyss positions itself as a universal context layer for AI tools and an MCP-connected workflow for context management. The source material does not spell out a full team or enterprise setup guide, so the safest interpretation is that it is designed for people who work across multiple apps and agents and need shared, current context.

Quick Facts

Category: AI context management
Platform: Web app with MCP access
Primary users: People working across multiple AI agents and work apps
Source domain: unabyss.com
Pricing: Free credits on signup; pay as you go after credits run out
Notable workflow: Connect sources, plug in an MCP client, choose access scope