Unabyss
Unabyss gives every AI agent one shared, live memory built from Slack, Gmail, Notion, and GitHub — so you stop re-explaining yourself.
Unabyss solves a problem most people don't have a name for yet: your AI tools are strangers to each other. If you pay for two or more AI subscriptions and keep pasting the same project brief, Pro at $13/mo billed annually ($15/mo monthly, 7-day free trial) is worth testing. The catch is setup — this is MCP plumbing, not a consumer app, and non-technical users will feel that. If you only run Claude plus one data source, skip it; the cross-agent value never materializes.
Verified 7d ago · liveness 84/100 · cite: rightaichoice.com/tools/unabyss
- Builders and vibe coders running Claude, Cursor, Codex, or Gemini who don't want to restate project conventions each
- Founders who want every AI tool they use already briefed on strategy, customers, and what shipped
- Agencies needing per-client context separation with sensitivity-based permission scopes
- GTM teams unifying pipeline, account notes, and call recordings from Fathom or Fireflies into one AI-readable memory
- Anyone using exactly one AI tool and one data source — the cross-agent value never materializes
- Enterprise teams needing on-premises or self-hosted deployment
- Non-technical users who don't want to authorize OAuth connections or handle MCP setup tokens
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Skip Unabyss if you run a single AI tool against a single data source — the shared-memory layer only pays off once two or more agents need the same picture.
Pro caps you at 3 connected agents via MCP and 20 connected accounts — a fourth agent or a 21st account means moving up to Max at $79/mo billed annually ($89/mo monthly).
At $13/mo billed annually ($15/mo monthly), Pro undercuts a ChatGPT Plus or Claude Pro add-on and fits a solo builder paying for two or three AI subscriptions. Max at $79/mo billed annually ($89/mo monthly) is priced against multi-agent power users, not casual ones. Team at $39/seat/mo billed annually ($49/seat/mo monthly) with a 3-seat minimum lands between per-seat dev tooling and enterprise context platforms.
In short
Unabyss — Unabyss gives every AI agent one shared, live memory built from Slack, Gmail, Notion, and GitHub — so you stop re-explaining yourself. Best for Builders and vibe coders running Claude, Cursor, Codex, or Gemini who don't want to restate project conventions each, Founders who want every AI tool they use already briefed on strategy, customers, and what shipped, Agencies needing per-client context separation with sensitivity-based permission scopes. Free to start; paid plans from $13/mo.
What's new in Unabyss
Checked 7 days agoAcross the latest 5 updates: 3 feature updates and 2 news mentions.
Benchmark: structured context cut Claude Code cost 36%, time 38%
Unabyss ran 20 tasks 60 times in Claude Code with and without pre-loaded structured context, reporting 36% lower cost, 38% less time and 8.9/10 versus 7.7 output quality in the structured runs.
Why Markdown files aren't enough to give AI memory
Vendor post argues plain-text context files go stale after about a week and positions Unabyss's live structured context as the fix.
v1.16.0 — Agent setup for Vellum, Hermes, and file-based agents
Adds dedicated setup for Vellum Assistant and Hermes; file-based agents now install the system prompt automatically.
v1.15.0 — Multiple Google accounts and Drive sync scope
Connect several Gmail, Drive and Calendar accounts, choose exactly what each Drive account syncs, and see clearer agent connection state during MCP setup.
v1.14.0 — Upload your files and connect your agent in onboarding
Adds file upload on Pick Your Apps, a Connect Your Agent onboarding step, past-due Team billing fixes, MCP docs layout changes and mobile-friendly agent cards.
What people actually say about Unabyss — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
16 mentions across 1 source (Product Hunt) · researched Jul 2, 2026.
Average across the 1 source that answered — each source counts once, not each post.
- +MCP-native architecture enables context portability across AI tools seamlessly.
- +Structured context files give users full ownership and ability to correct errors.
- +Three-layer segmentation (personal, professional, confidential) provides granular access control.
- +Intelligent compression reduces token usage up to 10x, lowering costs.
- +Continuous sync from multiple sources keeps context fresh with minimal manual effort.
- −No persistent memory across sessions — context layer only, not memory.
- −Unclear sync interval for context freshness — real-time or periodic?
- −No automatic adaptation to changing user roles or communication style.
- −Users lack tools to evaluate how well Unabyss connects data correctly.
- −No integration for WhatsApp Business, a primary tool in some regions.
- • No hidden costs reported; potential cost if exceeding free tier source limits.
Viability Score
How well maintained and how widely used is Unabyss? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- MCP server access for any MCP-compatible agent
- One-click Claude connect via the official connector
- One-click ChatGPT connect via the official plugin
- Context sync across 25+ apps including Slack, Gmail, Notion, and GitHub
- Structured memory tagged by topic, sensitivity, and source
- Intelligent context compression up to 10x token reduction
- Granular permission scopes: no restriction, exclude private, exclude confidential, exclude source
- MCP activity log tracking read, write, and auth events
- Shareable Skills Library pages for packaging context
- Obsidian two-way sync and Trello sync
- Multiple Google accounts for Gmail, Drive, and Calendar with per-account Drive sync scope
- File upload during onboarding plus a guided Connect your agent step
- Dedicated setup for Vellum Assistant and Hermes agents, with auto-installed system prompt for file-based agents
- Fathom meeting import via OAuth, plus Fireflies, tl;dv, and Granola meeting tools
- Website sync for public pages
About Unabyss
Unabyss is a universal context layer for AI agents. It pulls your work out of Slack, Gmail, Notion, GitHub, Google Drive, Calendar, meeting tools like Fathom, Fireflies, tl;dv and Granola, plus Obsidian, Linear, OneNote and X/Twitter — roughly 25 apps — and turns it into one structured memory that any MCP-compatible AI reads. Claude, ChatGPT, Cursor, Codex, Gemini, Antigravity, Perplexity, Grok, OpenCode, VS Code, Vellum and Hermes all pull from that same picture instead of starting each chat from zero. The differentiator is that it is a layer you own rather than memory locked inside one vendor: context is tagged by topic, sensitivity and source, filtered by permission scope (no restriction, exclude private, exclude confidential, exclude source), and served to each agent over MCP with an activity log of read, write and auth events. The company's own August 2026 benchmark of 20 coding tasks run 60 times in Claude Code found structured context cut cost 36% and time 38%, with output quality scoring 8.9/10 versus 7.7. Setup is the honest catch: this is MCP plumbing with OAuth connections and token handoffs, not a consumer app.
Behind the Verdict
Unabyss is betting that the memory problem is not a model problem but a plumbing problem. Instead of asking one assistant to remember harder, it builds a shared context layer that sits between your apps and every agent you use, then serves each one only the slice it needs over MCP. The mechanics are concrete. You connect sources once — Slack, Gmail, Notion, Google Drive, Calendar, GitHub, Linear, Obsidian, and meeting tools including Fathom, Fireflies, tl;dv and Granola — and Unabyss assembles a structured profile (role, project, focus, stack) plus tagged memory items. Every item carries a topic, a sensitivity label and a source, and you control what leaves the layer through four permission scopes: no restriction, exclude private, exclude confidential, exclude source. That granularity is the feature most competitors lack, and it is why agencies and GTM teams can use one account across clients without leaking the wrong account's notes. The 2026 roadmap has been execution-heavy rather than headline-heavy. v1.11.0 shipped one-click Claude connect via the official connector, plus Grok and more agents on /mcp and Fathom OAuth. v1.14.0 added file upload and a Connect Your Agent onboarding step. v1.15.0 added multiple Google accounts with per-account Drive sync scope. v1.16.0 added dedicated setup for Vellum Assistant and Hermes, with file-based agents installing the system prompt automatically. The changelog also shows the honest side of a young product: v1.11.2 fixed Fathom OAuth imports stuck at Starting, and v1.13.0 fixed Obsidian and Trello sync after Clear all context. Strengths: cross-agent reach (10+ AI tools, 25+ apps), sensitivity-based filtering, roughly 10x context compression via intelligent compression, the MCP activity log, and the fact that you can export and move your context between models. Weaknesses: setup requires OAuth authorization and an MCP token handoff, some integrations are still marked Soon (Trello, OneNote, Discord), and shared context is only as current as the last sync. The Team tier additionally requires a 3-seat minimum at $39/seat/mo billed annually ($49/seat/mo monthly), which rules out two-person shops. Where it fits: builders and vibe coders in Claude, Cursor, Codex or Gemini who restate conventions every session; founders and GTM teams whose strategy, pipeline and call notes live in five apps; agencies needing per-client separation. Where it does not: single-tool users, anyone needing on-prem or self-hosted deployment, and non-technical users who don't want to manage OAuth and tokens. SOC 2 Type II is listed as in progress, so security-review-heavy buyers should note it is not yet complete.
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Real-world workflow fit
Concrete scenarios for the personas Unabyss actually fits — and what changes day-one when you adopt it.
Connects GitHub, Linear, Notion and Slack once, then opens a new Claude Code session with MCP pointed at Unabyss.
Outcome: The agent starts with past decisions, repo conventions and open tickets already loaded instead of asking for a project brief; the vendor's own August 2026 benchmark of 20 tasks run 60 times reported 36% lower cost and 38% less time with structured context pre-loaded.
Separates each client's Slack, Drive and meeting notes, then applies the 'exclude confidential' or 'exclude source' permission scope per project before client-facing AI work.
Outcome: Every AI answer is grounded in the right account, and client-confidential files never enter the context served to the model.
Imports Fathom or Fireflies call recordings and connects Notion account notes plus Linear, then asks ChatGPT to draft follow-ups.
Outcome: Outreach drafts reference real call content and current pipeline state without manually pasting notes into the chat.
Use Cases
- Keep your AI coding agent updated with latest GitHub commits, Linear tickets, and Notion docs without manual prompting.
- Export your entire personal context map (meetings, emails, notes) to any LLM chat for more informed answers.
- Filter sensitive work emails and private calendar events when using AI in public demos or screen sharing.
- Sync meeting notes from Fathom, Fireflies, tl;dv, or Granola into your AI's context so it can answer questions about past conversations.
- Give your AI full access to your Google Drive and Slack archives, while excluding company confidential files.
- Agencies: keep each client's context separated, so every AI response is grounded in the right account.
Models Under the Hood
as of 2026-10-10
Limitations
- Unabyss connects AI agents over MCP and syncs context from your apps; some integrations are still marked 'Soon' (Trello, OneNote, Discord) and new integrations land regularly.
- Setup involves connecting an agent via MCP or an official one-click connector (e.g., Claude, ChatGPT), which can require technical configuration.
- Import/indexing issues have occurred historically (e.g., Fathom imports stuck at 'Starting', addressed in v1.11.2).
- SOC 2 Type II is listed as in progress, not complete.
as of 2026-10-04
Verification history
We have re-verified Unabyss 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Unabyss tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Solo user who wants to connect one or two sources and one agent to see whether structured context actually changes AI output before paying.
What this tier adds
Starting tier: 7-day free trial with no credit card required, enough to connect first sources and an agent and test context delivery.
Pro
$13/mo billed annually ($15/mo monthly)
Ideal for
Individual builder or founder paying for two or three AI subscriptions who wants Claude, ChatGPT and one more agent reading the same memory.
What this tier adds
Adds up to 3 connected agents via MCP, up to 20 connected accounts and the premium usage tier over the free entry point.
Max
$79/mo billed annually ($89/mo monthly)
Ideal for
Power user who lives in AI all day and runs coding agents, chat agents and voice or file-based tools that all need the same context.
What this tier adds
Over Pro: unlimited agents, unlimited connected accounts, multi-account support for Google apps, unlimited usage and early access to new features.
Team
$39/seat/mo billed annually ($49/seat/mo monthly)
Ideal for
Agency, GTM team or startup with at least three people who need one shared context workspace with central billing.
What this tier adds
Over Max: a shared team workspace, invite teammates by email and central seat and invoice management — with a 3-seat minimum.
Where the pricing makes sense
The company stage and team size where Unabyss's pricing actually pencils out — and where peers do it cheaper.
At $13/mo billed annually ($15/mo monthly), Pro undercuts a ChatGPT Plus or Claude Pro add-on and fits a solo builder paying for two or three AI subscriptions. Max at $79/mo billed annually ($89/mo monthly) is priced against multi-agent power users, not casual ones. Team at $39/seat/mo billed annually ($49/seat/mo monthly) with a 3-seat minimum lands between per-seat dev tooling and enterprise context platforms.
Setup time & first value
How long it actually takes to get something useful out of Unabyss — broken out by persona, not the marketing-page minute.
Builders in Claude or ChatGPT: roughly 10–15 minutes — one-click connector, one message, then connect sources. Cursor, Codex, Gemini or other MCP clients: 20–30 minutes including the three-step MCP handoff and token entry. Agencies and GTM teams: longer, because each source and each client scope needs its own permission review before you trust the output.
Switching to or from Unabyss
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From pasting context manually into ChatGPT or Claude: connect Unabyss once and agents read the same memory instead of the briefing you retype each session.
- →From a plain Markdown or plain-text context file: import through file upload during onboarding, then let Unabyss keep the structured items in sync from the connected sources.
- →From built-in vendor memory inside one assistant: use the Claude official connector or the ChatGPT plugin so context follows you into the other agents you already pay for.
- →From Obsidian notes: enable Obsidian two-way sync; if sync looks broken after Clear all context, the fix shipped in v1.13.0.
- →From Fathom meeting notes: authorize Fathom OAuth; imports hanging at 'Starting' were fixed in v1.11.2.
- ↗To a self-hosted context store: Unabyss is a hosted layer you own conceptually but connect over MCP, so on-prem teams are a stated non-fit.
- ↗To a single-assistant built-in memory: you lose the cross-agent reach and the sensitivity scopes, so this is a downgrade unless you drop to one AI tool.
- ↗To Markdown context files: possible if you export your tagged items, but the vendor argues plain-text files go stale within about a week.
- ↗To building your own MCP context server: viable if you have engineering time, but you rebuild sync connectors, permission scopes, the activity log and compression yourself.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Unabyss”, and we withheld 6: 6 could not be judged, because “Unabyss” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Unabyss.
Official links
Featured Head-to-Head Comparisons
Unabyss vs Spider Cloud
Spider Cloud wins for users needing fast, reliable web data extraction at scale, especially for RAG and AI agent training. Unabyss is better for those who want to unify their existing app data into AI context without manual syncing. Choose based on whether your bottleneck is external web data or internal fragmented context.
Unabyss vs Temporal Ai
Choose Temporal AI if you need rock-solid durability and recovery for multi-step AI workflows—especially with human-in-the-loop or Saga patterns. Unabyss wins when your pain is fragmented context across tools like Slack, Notion, and Gmail, and you want every AI agent (Claude, Cursor, ChatGPT) to see the same up-to-date picture. They solve different problems: reliability vs. context freshness.
Unabyss vs Presto Voice
If you run a QSR chain with drive-thrus and want to boost revenue via voice AI, Presto Voice is the clear pick — it's purpose-built for that use case with proven ROI. If you're a builder or knowledge worker juggling multiple AI agents and data sources, Unabyss solves the stale-context problem with a self-updating, MCP-connected layer. They serve entirely different needs; choose based on your domain.
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