YourMemory
Local-first persistent memory for AI agents with a forgetting curve, open source and MCP-compatible.
Pick YourMemory if you want persistent agent memory you can inspect, self-host, and verify. The headline numbers — 89.4% Recall@5 on LongMemEval and an 84% token-waste reduction at 30 sessions — ship with benchmark code in the repo, and the +16pp LoCoMo lead over Mem0 is the kind of claim most memory vendors won't put a number on. Running locally with no API key plus a Memory Browser and hash-chained audit log gives you visibility most memory layers don't: you can see what your agent remembers, its live strength, and every read and delete. The trade-offs are real — the free tier is local-only, integration is MCP-only across 7 clients, and Enterprise team memory is a private build. If you
Verified 1d ago · liveness 75/100 · cite: rightaichoice.com/tools/yourmemory
- Developers building agentic AI applications
- Privacy-conscious developers wanting local-only memory
- Cost-focused developers cutting redundant context resends
- AI researchers needing reproducible benchmarks
- Non-technical users who can't run a local Python service
- Users needing a fully managed cloud solution
- Teams needing a polished UI for non-developer end users
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Skip YourMemory if you need a fully managed cloud memory service with a polished end-user UI, or if your stack's AI clients sit outside the 7 MCP clients it supports.
Shared organizational memory — the feature that turns individual recall into a team asset — sits behind the Enterprise private build, so the free local tier doesn't cover multi-person use.
YourMemory's published free tier is $0/mo and fully functional for a single developer running local memory — the forgetting curve, Memory Browser, hash-chained audit trail, Instant Audit prompt, and token calculator are all included, open source, with no API key. That lands it well below managed cloud memory layers like Mem0 and Zep, where persistent cross-session memory typically rides on a paid usage plan. Enterprise shared team memory is a private build, priced by contact, so budget for a
In short
YourMemory — Local-first persistent memory for AI agents with a forgetting curve, open source and MCP-compatible. Best for Developers building agentic AI applications, Privacy-conscious developers wanting local-only memory, Cost-focused developers cutting redundant context resends. Free to use.
What's new in YourMemory
Checked 8 days agoAcross the latest 1 update: 1 feature update.
What people actually say about YourMemory — 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.
26 mentions across 4 sources (Hacker News, YouTube, Product Hunt, GitHub) · researched Jul 31, 2026.
Average across the 4 sources that answered — each source counts once, not each post.
- +Biologically-inspired Ebbinghaus decay cuts token waste by 84% over 30 sessions
- +89.4% Recall@5 on LongMemEval, +16pp over Mem0 on LoCoMo
- +Local, no API key, privacy-first: data never leaves your machine
- +Activity-aware decay adapts to actual usage rather than wall-clock time
- +MCP-compatible with 7 clients, broad integration potential
- −Forgetting curve may drop load-bearing architectural decisions
- −Requires manual audit prompt injection per chat, not fully automatic
- −Limited integrations beyond MCP; lacks auto-setup for Opencode.ai
- −Early-stage: only 261 stars, 10 open issues, small community
- −Benchmarks self-reported; independent verification limited
- • No hidden costs reported; open-source base, enterprise only for team features
Viability Score
How well maintained and how widely used is YourMemory? 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
- Ebbinghaus-inspired forgetting curve for memory decay
- Importance-based memory scoring with reinforcement on recall
- Memory lifecycle: born, stored, linked, recalled, faded
- 89.4% Recall@5 on LongMemEval, benchmark code in repo
- 84% token waste reduction measured over 30 sessions
- +16pp recall versus Mem0 on LoCoMo
- MCP compatible with 7 clients including Claude, ChatGPT, Gemini, Cursor, Copilot
- Memory Browser showing live strength, category, importance, recall count
- Audit tab with tamper-evident hash chain and 90-day retention
- Instant Audit prompt pasteable into any chat session, no YourMemory knowledge required
- Browser-based token savings calculator over exported chat history
- Local-first: runs on your machine with no API key and no data leaving it
- Open source on GitHub
- Three-command activation: pip install yourmemory, yourmemory-register, yourmemory-setup
- Enterprise shared team memory across an organization (private build)
About YourMemory
YourMemory is a memory layer you run on your own machine that gives AI agents persistent recall. It stores what matters, links related knowledge, and fades what stops being used — modeled on an Ebbinghaus-inspired forgetting curve where memories are scored by importance and recency, decay over time, and strengthen when recalled. It plugs into 7 MCP clients, including Claude, ChatGPT, Gemini, Cursor, and Copilot, so the agents you already use can carry context across sessions instead of starting from zero. Setup is a three-command flow: pip install yourmemory, yourmemory-register with an activation token, then yourmemory-setup. YourMemory publishes reproducible benchmark numbers rather than marketing claims: 89.4% Recall@5 on LongMemEval, an 84% reduction in token waste measured over 30 sessions, and +16pp recall versus Mem0 on LoCoMo, with benchmark code living in the repo. A Memory Browser at localhost:3033/ui shows each stored memory with its live strength percentage, category, importance, recall count, and last-accessed time, and an Audit tab logs every read, write, and delete to a tamper-evident hash chain with 90-day retention. Two savings tools ship with it — a 30-second Instant Audit prompt you paste at the end of any chat session, and a token savings calculator that tokenizes an exported chat history entirely in your browser, uploading nothing. It is aimed at developers building agentic apps and privacy-conscious teams who don't want a cloud memory service holding their data, and Enterprise adds shared team memory distributed as a private build.
Behind the Verdict
YourMemory's pitch is narrower and more honest than most memory-layer marketing: it does one job — persistent, decaying recall for AI agents — and it measures that job on public datasets instead of writing adjectives. The Ebbinghaus-inspired forgetting curve is the actual differentiator. Memories are born with an importance score, linked to related knowledge, reinforced each time they're recalled, and faded when they sit unused, which is a meaningfully different design from a vector store that hoards every chunk forever and returns whichever chunks match a query. The comparison table on the homepage draws that line explicitly: vector DBs return chunks and never prioritize or forget; YourMemory keeps facts that merge, decay, and connect. The Memory Browser is where that abstraction becomes visible — you can watch a memory's strength percentage drop as it ages and jump back up after it's recalled, and see recalls, importance, category, and last-accessed on each entry. The Audit tab extends that into compliance territory with a tamper-evident hash chain covering every read, write, and delete at 90-day retention, which is more than most local-first tools bother to build. Benchmarks are the second leg: 89.4% Recall@5 on LongMemEval, 84% less token waste over 30 sessions, and +16pp recall against Mem0 on LoCoMo, all with benchmark code in the repo. The 84% token number matters practically — instead of re-sending growing chat history each turn, the agent injects a flat set of recalled memories, so context cost stops compounding. Two supporting tools reinforce the cost story: a 30-second Instant Audit prompt you paste into Claude, ChatGPT, Gemini, Cursor, or Copilot (which needs no knowledge of YourMemory and has the AI measure and compress its own conversation), and a calculator that tokenizes an exported chat history entirely in your browser. That local-only tokenization is consistent with the rest of the product's posture — no API key, no data leaving your machine. Setup is deliberately minimal: pip install, register with an emailed 6-digit-code token, run setup, and the UI is live at localhost:3033/ui. Where YourMemory is weakest is scope. It is a memory layer, not an assistant — you still bring Claude, ChatGPT, Gemini, Cursor, or Copilot, and you integrate via MCP. The free tier is local-only per the published details, Enterprise shared team memory is distributed as a private build rather than something you configure yourself, and the Memory Browser and Audit views are developer-facing panels rather than a polished product UI. If your need is a managed cloud memory service with an end-user interface, Mem0 and Zep are the better fits. If your need is agent memory you can inspect line by line, verify against a hash chain, and run without a data-egress conversation, YourMemory is the more interesting choice.
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Real-world workflow fit
Concrete scenarios for the personas YourMemory actually fits — and what changes day-one when you adopt it.
Installs YourMemory with pip install yourmemory, registers with an emailed activation token, runs yourmemory-setup, and connects Claude over MCP. Memories accumulate across sessions; unused ones fade, and preferences that keep coming up hold their strength in the Memory Browser.
Outcome: The assistant carries context between sessions without re-sending full chat history, and the developer can see each memory's live strength and recall count at localhost:3033/ui.
Exports an existing AI chat history and pastes it into the browser-based token savings calculator — tokenized locally, nothing uploaded — to size the token waste. Then pastes the 30-second Instant Audit prompt at the end of a Cursor session to have the AI measure and compress its own conversation.
Outcome: A concrete before/after token and dollar number for the same workflow, matching the 84% token-waste reduction YourMemory reports over 30 sessions.
Engineer A solves a customer edge case in a session; with Enterprise shared memory the resolution persists with the org and surfaces automatically when Engineer B opens a session and recalls the same topic.
Outcome: Engineer B picks up a 6-day-old solved edge case in minutes instead of reconstructing two hours of debugging, with the recall event logged in the audit chain.
Use Cases
- Developers building AI agents that need to remember user preferences across sessions
- Cutting token costs by injecting a flat set of recalled memories instead of re-sending full history
- Privacy-conscious developers who want AI chat memory to stay entirely local
- AI researchers who need reproducible memory benchmarks and open benchmark code
- Solo developers building a personal assistant that keeps context between sessions
- Startups prototyping agentic apps without adding a cloud memory dependency
- Engineering teams sharing solved edge cases across AI sessions (Enterprise)
- Auditing exactly what an agent read, wrote, or deleted from memory
Models Under the Hood
as of 2026-10-17
Limitations
- YourMemory is an open-source, local-first memory layer, not a standalone assistant — you still bring Claude, ChatGPT, Gemini, Cursor, or Copilot and connect through MCP.
- Agent integration is MCP-only across 7 supported clients, so anything outside that set isn't covered.
- The Memory Browser and Audit views at localhost:3033/ui are developer-facing panels rather than an end-user product UI, and running the service assumes you're comfortable with a local Python install and the three-command activation flow.
- The published free tier is local-only memory; shared organizational memory is Enterprise, distributed as a private build rather than something you configure through the product itself.
- Vector-store users expecting chunk retrieval semantics will find the decay-and-reinforce model behaves differently by design.
as of 2026-10-10
Verification history
We have re-verified YourMemory 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-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
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 YourMemory 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 developer or privacy-conscious builder running memory on their own machine and connecting existing AI clients over MCP.
What this tier adds
Starting tier: fully functional persistent memory at $0/mo — forgetting curve, Memory Browser, hash-chained audit trail, Instant Audit prompt, token calculator, 7 MCP clients, open source, no API key.
Enterprise
Contact
Ideal for
Engineering org that needs solved edge cases and accumulated knowledge to persist across teammates rather than evaporate when a session closes.
What this tier adds
Adds shared team memory across your organization and a private build, with per-member private and shared memory, priced by contact.
Where the pricing makes sense
The company stage and team size where YourMemory's pricing actually pencils out — and where peers do it cheaper.
YourMemory's published free tier is $0/mo and fully functional for a single developer running local memory — the forgetting curve, Memory Browser, hash-chained audit trail, Instant Audit prompt, and token calculator are all included, open source, with no API key. That lands it well below managed cloud memory layers like Mem0 and Zep, where persistent cross-session memory typically rides on a paid usage plan. Enterprise shared team memory is a private build, priced by contact, so budget for a
Setup time & first value
How long it actually takes to get something useful out of YourMemory — broken out by persona, not the marketing-page minute.
Solo developer: under 2 minutes end-to-end — pip install yourmemory, yourmemory-register with the activation token from the emailed 6-digit verification code, then yourmemory-setup, and the UI is live at localhost:3033/ui. First value arrives as soon as an MCP-connected client starts writing memories. Enterprise shared team memory takes longer because it's distributed as a private build rather
Switching to or from YourMemory
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Mem0: keep your existing MCP-connected clients and point them at YourMemory instead — the same Claude, ChatGPT, Gemini, Cursor, and Copilot sessions carry over, while memory moves to a local store you can browse at
- →From a plain vector store: swap chunk retrieval for the decay-and-reinforce model, which stores facts that merge and fade rather than hoarding every chunk, so recall stays flat instead of growing with history.
- →From no memory layer at all: run the three-command activation and let the agents you already use start writing memories — no API key and no data leaving your machine.
- ↗To a managed cloud memory service (Mem0, Zep): move off local-first if you need a fully managed backend with a polished end-user UI rather than developer-facing Memory Browser and Audit panels.
- ↗To no memory layer: stop the local service and your agents return to starting each session from zero, with the token-cost compounding that follows.
- ↗Out of Enterprise shared memory: reverting to the free local tier means each member's memories stay private per machine instead of surfacing across the org.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “YourMemory”, and we withheld 6: 6 could not be judged, because “YourMemory” 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 YourMemory.
Official links
Tools that pair well with YourMemory
Common stack mates teams adopt alongside YourMemory, with the specific reason each pairing earns its keep.
Agentmemory
Open-source memory runtime that gives coding agents persistent recall between sessions, stored on your machine.
Mempalace
Open-source local-first AI memory that stores every conversation verbatim in a method-of-loci palace on your machine.
Powermem
Open-source, self-hosted memory layer that gives AI agents persistent recall via hybrid retrieval.
Featured Head-to-Head Comparisons
Yourmemory vs Spider Cloud
Choose Spider Cloud if you need high-performance, real-time web data extraction for AI agents or RAG pipelines, with a 99.9% success rate and low per-page cost. Choose YourMemory if you want a biologically-inspired persistent memory layer that runs locally, reduces token waste by 84%, and gives your agents long-term recall without sending data externally. They solve different problems: one feeds agents data from the web, the other helps agents remember past conversations.
Yourmemory vs Presto Voice
Presto Voice and YourMemory serve completely different needs. Presto Voice is a vertical SaaS for QSR drive-thrus, automating orders with voice AI and upselling—proven with chains like Dairy Queen. YourMemory is an open-source developer tool for persistent memory in AI agents, reducing token waste and mimicking human forgetting. Choose based on your domain: restaurant operations or AI application development.
Yourmemory vs Temporal Ai
Temporal AI is the clear choice for teams needing robust, fault-tolerant orchestration of AI agents and long-running workflows, especially with human-in-the-loop and Saga patterns. YourMemory excels for developers wanting a lightweight, local memory layer that reduces token costs and mimics human forgetting. Choose Temporal for reliability at scale; choose YourMemory for efficient, privacy-focused memory in agentic apps.
Alternatives to YourMemory
View allAgentmemory
Open-source memory runtime that gives coding agents persistent recall between sessions, stored on your machine.
Frequently Asked Questions
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