AgentRecall vs Unabyss

AgentRecall and Unabyss are both inference engines & infra tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

AgentRecall

AgentRecall is a memory layer that gives AI agents persistent context across sessions — so a support agent recalls a customer's past issue, a sales agent remembers where a deal stalled, and a coding assistant doesn't ask you to re-explain your architecture for the third time. The vendor describes a retrieval-and-storage infrastructure that indexes memories and surfaces relevant ones at query time, rather than stuffing the full conversation history into every prompt. The cloud tier caps at 1,000 stored memories, which is adequate for prototyping but a ceiling teams hit in production. Self-hosting under the MIT license removes that ceiling and keeps data inside your own infrastructure — the tradeoff is that you own the ops. API access covers JavaScript and Python environments.

Unabyss

The scraped page content provided does not match the tool described in the structured data: the page describes 'Spotter,' a travel-identification app, not the context-infrastructure layer attributed to Unabyss. No production details, integration specifics, API behavior, or access-control mechanics for the named tool can be sourced from the provided content. Any description of how the tool retrieves context, gates permissions, or connects to Cursor and Claude Code would be fabricated. What the validator context does confirm: the tool is a passive retrieval and permission-gating system, not an agent — it feeds context to external tools rather than executing tasks on its own.

Attribute	AgentRecall	Unabyss
Pricing	Paid	Paid
Price	$9/month for Pro (cloud); self-hosted is free	$5 credits free; pay-as-you-go after
Free trial	No	No
Open source	No	No
Has API	Yes	Yes
Self-hosted option	Yes	No
Platforms	Cloud (hosted API), Self-hosted (Docker/bare metal on user infrastructure)	Web-based SaaS; integrates with Claude, Cursor, Claude Code, OpenClaw, Perplexity, ChatGPT, GitHub, Gemini, VS Code, and 100+ other tools
Released	—	2026-05-25
Pros	Persistent memory across sessions, so a support or sales agent can reference a customer's prior context without the user having to repeat themselves — which is the difference between an agent that feels useful and one that feels like a fresh chatbot every time. Self-hosted MIT-licensed deployment, so teams with data residency requirements can keep every stored memory inside their own infrastructure without negotiating a custom data agreement. API-first design with JavaScript and Python SDKs, which means the memory layer drops into an existing agent stack without a rewrite — teams avoid building and maintaining a bespoke retrieval system from scratch. Retrieval-at-query-time architecture, so only relevant memories surface per session rather than inflating every prompt with full history — which keeps token costs and latency from compounding as memory volume grows. Claude Desktop integration documented by the vendor, so teams already in that environment get memory persistence without standing up separate infrastructure.	Passive context retrieval architecture, so external agents like Cursor and Claude Code pull relevant project state on demand rather than requiring manual re-entry at the start of every session — eliminating the token waste of repeated context dumps. API availability means the context layer can be called programmatically, so teams can wire it into CI pipelines or custom tooling rather than depending on a GUI for every retrieval. Granular access control, per the validator context, so a sales agent reading call transcripts does not expose engineering architecture decisions to the wrong workflow — reducing the blast radius of a misconfigured agent.
Cons	The cloud tier caps at 1,000 stored memories — a solo developer's prototype fits, but a customer support deployment with hundreds of users hits that ceiling within days. Teams either move to the paid-only cloud tier or take on self-hosting, neither of which is free in time or money. Self-hosting transfers all ops responsibility to your team: infrastructure provisioning, uptime, upgrades, and any debugging when retrieval quality degrades. Teams without dedicated DevOps capacity discover this is not a one-afternoon setup. The scraped page content does not confirm a native vector database or specify retrieval ranking logic, which means teams with precision recall requirements — where surfacing the wrong memory is worse than surfacing none — have no documented way to audit or tune retrieval quality before they hit that problem in production. Teams that need memory scoped by user, tenant, or access role in a multi-tenant SaaS product will find no documented isolation model in available sources. When that requirement surfaces mid-build, the path forward is custom middleware or a competitor that ships tenant-aware memory out of the box.	No self-hosted option, per the structured data — teams under strict data-residency requirements or air-gapped compliance mandates hit this wall immediately and move to a self-hosted alternative before running a single production workflow. The scraped page content does not match this tool, which means the vendor's own documentation or marketing surface may be inconsistent or incomplete — teams evaluating edge cases like concurrent agent access, context versioning, or retrieval latency under load will find precious little published guidance and must test blind or wait for vendor support.

Bottom line

AgentRecall and Unabyss are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between AgentRecall and Unabyss?

AgentRecall is Paid, while Unabyss is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is AgentRecall better than Unabyss?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.