Stash is live · free · last verified 24 Oct 2026 · viability monitor
Stash
Stash is a shared memory your connected AI tools can recall in the next conversation.
Stash earns its place if you genuinely hop between AI tools and keep re-typing the same preferences into each one. The supported set named on the site — Claude Desktop, Claude Code, Cursor, OpenCode and Replit — plus the recall loop it demonstrates (tell your AI, save to Stash, start a new chat) make this a real workflow rather than a landing-page abstraction. Default-private storage you can ask your AI to edit is the second reason to pick it over relying only on one assistant's built-in memory. The honest catch: value scales with how many of those tools you actually use, and the site states plainly that recall depends on your connected AI tool using Stash. If one assistant already covers
Verdict generatedVerified 5d ago · liveness 67/100 · cite: rightaichoice.com/tools/stash
- Individual AI users running three or more assistants
- Writers who want tone and style remembered
- Learners who save their level once instead of restating it
- Anyone who wants to inspect and edit what their AI remembers
- People who use a single AI tool and don't need cross-tool memory
- Teams wanting shared, multi-user memory administration
- Users whose daily AI tools aren't in the supported set
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Skip Stash if you work inside a single AI assistant all day, or if your daily tools fall outside Claude Desktop, Claude Code, Cursor, OpenCode and Replit — there is nothing to port between.
Stash is aimed at individual AI users rather than teams or companies, and the site's own framing is a personal memory URL rather than seats or admin controls. Compare it against the cost of the assistants you already pay for: if you run Claude Desktop, Claude Code, Cursor and Replit at once, Stash is a small add-on to that stack, but it stacks on top of them rather than replacing any of them.
In short
Stash — Stash is a shared memory your connected AI tools can recall in the next conversation. Best for Individual AI users running three or more assistants, Writers who want tone and style remembered, Learners who save their level once instead of restating it. Free to use.
What is Stash?
Stash — Stash is a shared memory your connected AI tools can recall in the next conversation. Best for Individual AI users running three or more assistants, Writers who want tone and style remembered, Learners who save their level once instead of restating it. Free to use.
Stash is a shared memory layer that sits alongside the AI tools you already use. You tell your AI something worth keeping — your writing tone, a dietary preference, a learning level, a project plan — and Stash saves it so a later conversation starts from that point instead of from scratch. It works across connected tools: the site names Claude Desktop, Claude Code, Cursor, OpenCode and Replit, so context you save in one can be available in another rather than being trapped inside a single vendor's assistant. Setup is light. You sign in with Google to get a personal memory URL, pick your tool, and follow that tool's setup guide. From there the workflow is a three-step loop the vendor demonstrates on its own site: tell your AI a preference, it saves to your Stash, then start a new chat and ask it to recall that preference. The homepage's worked example is a saved note — 'I'm vegetarian and prefer quick meals' — resurfacing as a 15-minute chickpea stir-fry suggestion in a fresh conversation. Control is user-side. Memory is private by default and you ask your AI to inspect, update or remove what it remembers. It's aimed at individuals who use AI daily for writing, learning and planning and switch between assistants, rather than at teams wanting a shared multi-user memory store.
Key features
- Shared memory across connected AI tools
- Save preferences, plans and details once for later recall
- Sign in with Google to get a personal memory URL
- Connect Claude Desktop
- Connect Claude Code
- Connect Cursor
- Connect OpenCode
- Connect Replit
- Recall saved context in a brand-new conversation
- Carry context when you switch between AI tools
- Memory private by default
- Ask your AI to inspect what it remembers
- Ask your AI to update or remove remembered items
- Worked examples for writing, learning and planning
- Side-by-side without-Stash vs with-Stash comparison
Behind the verdict
Stash is best understood as a portability layer, not another assistant. It does not ship its own models, and the homepage says so in as many words: recall depends on your connected AI tool using Stash. What you get instead is a single place your context lives while you move between Claude Desktop, Claude Code, Cursor, OpenCode and Replit. Strengths. The onboarding is short and specific — sign in with Google, receive a personal memory URL, choose a tool, follow that tool's setup guide. The site then demonstrates the loop concretely with three examples across writing, learning and planning, and shows side-by-side what a conversation looks like with and without saved context. The vegetarian example ('I'm vegetarian and prefer quick meals' returning a 15-minute chickpea stir-fry) is a clear illustration of the intended payoff. Privacy defaults are user-side and legible: memory is private by default, and you ask your AI to inspect, update or remove what it remembers, so pruning is a conversation rather than a settings hunt. Weaknesses. Memory is added deliberately — you tell your AI to remember something — rather than captured automatically in the background. That is a real behavioural tax: if you forget to save, nothing carries over. Coverage is bounded by the five named tools, and the cross-tool benefit collapses if your daily stack sits outside them. And the model is personal, with a personal memory URL rather than a shared team workspace with multiple users and admin controls, so a team that wants one collective memory store is looking at the wrong product. Where it fits. Individuals who run three or more AI assistants and notice themselves restating tone, reading level or project context in each one. Writers protecting a voice. Learners who set their level once. Anyone who wants to see and edit what has been kept on their behalf. Where it doesn't. Single-tool users, teams needing shared memory administration, and anyone whose assistants aren't in the supported set. If you want memory that appears without you asking for it, Stash is deliberately the opposite of that.
Limitations
- Stash stores and returns memory; it does not include its own AI models, so it depends on a connected tool actually using it.
- The homepage states this directly: recall depends on your connected AI tool using Stash.
- Supported tools named on the site are Claude Desktop, Claude Code, Cursor, OpenCode and Replit — if your daily stack sits outside that set, the cross-tool benefit doesn't apply.
- Memory is added deliberately, by telling your AI to remember something, rather than being captured automatically in the background.
- The experience is also a personal one — there is a personal memory URL, not a shared team workspace with multiple users and admin controls.
as of 2026-10-14
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Is Stash still active?
Stash is live · free · last verified 24 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is Stash? 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 →What do users say about Stash?
What people actually say about Stash — 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.
Researched33 mentions across 7 sources (Hacker News, YouTube, Product Hunt, App Store, Stack Overflow, GitHub, Lemmy), 75 more we could not attribute · researched Sep 14, 2026.
Weighted by the 108 posts each of 7 sources contributed.
- +PostgreSQL backend means memory is durable, queryable, and inspectable with plain SQL
- +Self-hosted single binary with no cloud lock-in satisfies privacy-first and compliance-minded teams
- +MCP server integration slots into modern agent frameworks without bespoke glue
- +Episode logging plus fact extraction covers both raw history and distilled long-term memory
- +Open source lets you audit, fork, and extend the memory model to your own schema
- −No verified community reviews for this specific tool in the collected data
- −Requires Postgres operational knowledge that many app developers lack
- −Advanced skill level and no managed option raise the barrier for small teams
- −MCP dependency ties adoption to a fast-moving, still-immature protocol
- −Name collision with git stash, Stash investing, and stashapp muddies search and support
- • You pay for your own Postgres hosting, backups, and monitoring
- • Engineering time for Postgres schema tuning and MCP wiring
- • Upgrade and migration maintenance on your own infrastructure
- • Potential paid-tier limits that are unspecified in the provided data
How we verified this
Every listed fact about Stash— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 24 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Stash 12 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.
- — changed hidden costs, summary, setup time, our verdict, switching in, pricing fit, switching out, features, who should skip it, description
- — changed link health
- — changed switching out, who should skip it, who it suits, use cases, pricing tiers, pricing fit, setup time, our verdict, summary, features, hidden costs, description, limitations, switching in, integrations
- — changed SSL certificate
- — changed SSL certificate
- — changed hidden costs, our verdict, description, summary, pricing fit, setup time, who should skip it
Showing the 6 most recent of 12 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Stash cost in 2026?
Stash: Free to use. Pricing last verified 24 Oct 2026.
Plans compared
Every published Stash tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Free | Free | — | An individual AI user who runs two or more of the supported tools and wants to test whether shared recall actually saves them briefing time.Adds: Starting tier — sign in with Google, get a personal memory URL, connect compatible AI tools, and save preferences for recall in later conversations. |
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.
Where the pricing makes sense
The company stage and team size where Stash's pricing actually pencils out — and where peers do it cheaper.
Stash is aimed at individual AI users rather than teams or companies, and the site's own framing is a personal memory URL rather than seats or admin controls. Compare it against the cost of the assistants you already pay for: if you run Claude Desktop, Claude Code, Cursor and Replit at once, Stash is a small add-on to that stack, but it stacks on top of them rather than replacing any of them.
Has Stash's pricing changed?
No plan price for Stash has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Stash?
Pick Stash if you are Individual AI users running three or more assistants, Writers who want tone and style remembered, Learners who save their level once instead of restating it, Anyone who wants to inspect and edit what their AI remembers.
Look elsewhere if you are People who use a single AI tool and don't need cross-tool memory, Teams wanting shared, multi-user memory administration, Users whose daily AI tools aren't in the supported set, People who want memory captured with no setup or prompting at all.
Skip it if Skip Stash if you work inside a single AI assistant all day, or if your daily tools fall outside Claude Desktop, Claude Code, Cursor, OpenCode and Replit — there is nothing to port between.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Stash actually fits — and what changes day-one when you adopt it.
Tells the assistant to remember 'I like warm, concise emails. Skip formal greetings and get to the point.' That note lands in Stash, then the same preference is recalled when a drafting session starts in a second connected tool.
Outcome: A follow-up email opens in the right tone without a formality-and-length briefing first — the site's own worked example of the loop.
Saves their current level once, then starts a fresh conversation and asks the assistant to recall it before requesting an explanation.
Outcome: Explanations arrive pitched at the right depth instead of restarting at beginner level in every new chat.
Stores the project plan in Stash, then brings that context along when the work shifts to a different connected tool.
Outcome: The plan travels with the work instead of being re-explained each time the tool changes.
Use cases
- Keep your email tone and writing style on hand so a new chat opens in your voice instead of asking about formality
- Save a dietary or food preference once and have a fresh conversation recall it when you ask what to cook
- Store your learning level so a new assistant pitches explanations at the right depth
- Carry project plans between Claude Desktop, Cursor and Replit as your work moves tools
- Keep everyday preferences available for planning conversations without re-briefing each assistant
- Inspect and prune what your AI has stored so your memory stays accurate over time
Setup time & first value
How long it actually takes to get something useful out of Stash — broken out by persona, not the marketing-page minute.
Signing in with Google to get a personal memory URL takes a minute; the rest is following your chosen tool's own setup guide, plus one round of telling your AI something worth keeping and recalling it in a new conversation to confirm the loop works. Budget a few minutes per connected tool.
Switching to or from Stash
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From one assistant's built-in memory: save the preferences you rely on as explicit notes in Stash, then recall them from a new conversation in a second connected tool.
- →From re-typing context into every chat: start by saving tone, level and current-project details, since those are the notes that resurface most often.
- →From a plain document of your standing instructions: move the entries you actually restate into Stash so a connected tool can pull them into the conversation.
- ↗To a single-assistant memory: keep the same notes but accept they will only be recalled inside that one tool.
- ↗To a team memory workspace: Stash is a personal memory URL, so a multi-user store with admin controls requires a different product.
- ↗To no memory layer: copy the notes you want to keep into your own document before letting the Stash lapse.
Integrations
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Stash”, and we withheld 6: 6 could not be judged, because “Stash” 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 Stash.
Official links
What are the best Stash alternatives?
The closest alternatives to Stash we list are MemU, Caura Memclaw and Cognee. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| MemU | Freemium | Pricing not published | — |
| Caura Memclaw | Freemium | Pricing not published | — |
| Cognee | Freemium | Pricing not published | — |
Alternatives to Stash
View all
MemU
memU gives Codex, Claude, Cursor and other agents one shared, inspectable memory layer with source-linked recall.
Caura Memclaw
Governed shared memory for AI agent fleets — scoped writes, keystone policies and a per-recall audit trail.
Tools that pair well with Stash
Common stack mates teams adopt alongside Stash, with the specific reason each pairing earns its keep.
MemU
memU gives Codex, Claude, Cursor and other agents one shared, inspectable memory layer with source-linked recall.
Caura Memclaw
Governed shared memory for AI agent fleets — scoped writes, keystone policies and a per-recall audit trail.
Cognee
Cognee gives AI agents persistent knowledge-graph memory with cited recall across sessions, teams, and tools.
Stash vs its closest rival
Stash's closest head-to-head is with Spider Cloud — Choose Spider Cloud if you need to feed web data into AI agents—its Rust engine, 99.9% success, and new Browser AI commands make it cost-effective for RAG pipelines. Choose Stash if you need a self-hosted memory layer for agents that persist conversations, facts, and state in Postgres—best for privacy-first or offline autonomous systems. They solve different problems: one fetches data, the other remembers it. Verdict generated
Head-to-head comparisons
Stash vs Spider Cloud
Choose Spider Cloud if you need to feed web data into AI agents—its Rust engine, 99.9% success, and new Browser AI commands make it cost-effective for RAG pipelines. Choose Stash if you need a self-hosted memory layer for agents that persist conversations, facts, and state in Postgres—best for privacy-first or offline autonomous systems. They solve different problems: one fetches data, the other remembers it.
GeneratedStash vs Presto Voice
Don't buy on the fence: Presto Voice is a specialized drive-thru AI for QSR chains wanting proven revenue lift (up to 6% monthly) and 95% automation — but it's contact-priced and not for non-drive-thru businesses. Stash is a free, self-hosted memory for AI agent developers, not a restaurant tool. Your choice depends entirely on your domain: either you run a multi-location QSR or you code autonomous agents.
GeneratedStash vs Temporal Ai
Temporal is the right choice if you need an industrial-grade orchestration platform with retries, rollbacks, and human-in-the-loop for complex workflows (AI agents, microservices). Stash is perfect for developers who want a lightweight, self-hosted memory layer for AI agents, using Postgres with zero vendor lock-in. Pick Temporal for reliability at scale; pick Stash for simple, privacy-first agent memory.
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