YourMemory is a persistent memory system for AI agents that helps assistants retain useful context across sessions. It runs locally, supports MCP compatibility, and includes tools for memory review, audit logging, and cost analysis.
YourMemory is a persistent memory system for AI agents. It is designed to help assistants retain useful information across sessions instead of resetting to zero after every conversation.
The product describes its memory as biologically inspired: memories strengthen when recalled, fade when unused, and connect to one another through a hybrid graph and vector retrieval approach. The site positions this as a way to keep long-term context available without carrying forward everything indefinitely.
The homepage emphasizes practical workflow support. Users can estimate token savings with a prompt-based audit, review stored memories in a browser, and inspect a tamper-evident audit trail of memory operations. A free activation flow is available, and the site says the system runs locally with no API key required.
For teams, YourMemory also offers an Enterprise build for shared memory across an organization. The site frames this as a way to preserve solved issues, customer details, and architectural decisions so later sessions can surface relevant knowledge automatically.
YourMemory models memory as something that can strengthen when recalled and fade when left unused, instead of storing every item indefinitely. The homepage presents this as a lifecycle that keeps only the most relevant information active.
The product combines graph-style linking with vector retrieval so memories can connect across sessions rather than remain isolated chunks. The site contrasts this with legacy vector databases that return chunks without prioritization or forgetting.
The homepage highlights benchmarked results across three public datasets and calls out 89.4% Recall@5 on LongMemEval in the meta description. It also says the results are reproducible and that benchmark code is available in the repo.
YourMemory includes an instant audit prompt that can be pasted into Claude, ChatGPT, Gemini, Cursor, or Copilot to estimate savings from a conversation. It can also calculate token and cost impact from an exported chat history in the browser.
The interface includes a Memory Browser for reviewing stored memories, strength, category, and recall history, plus an Audit tab that logs reads, writes, and deletes in a tamper-evident hash chain.
The site offers a free activation flow that runs locally, requires no API key, and provides a token for command-line setup. It also links to a GitHub repo and Discord community.
Use YourMemory when you want an assistant that remembers prior preferences, decisions, or project details after the current chat ends. The product is built around carrying relevant context forward across sessions.
Use the Memory Browser and audit trail when you need to review what was stored, how strong a memory is, and when it was last recalled. This is useful for checking why a memory appears in later sessions.
Use the cost audit flow before or after a conversation to estimate how much context you are re-sending over time. The site offers both a quick prompt-based check and a browser-side calculation from exported chat history.
Use the Enterprise build when a team wants shared memory for repeated customer issues, architecture decisions, or internal knowledge. The homepage shows shared and private memory states and describes the enterprise version as a private build.
Use the setup flow if you want a local installation that does not depend on an external API key. The site says activation takes under two minutes and provides a command-line token after email verification.
YourMemory offers a free activation flow and runs locally on your machine. The site says it starts in under 2 minutes and does not require an API key.
The homepage describes YourMemory as compatible with MCP and shows example use with Claude, ChatGPT, Gemini, Cursor, and Copilot in its memory-audit workflow. No broader integration catalog is listed on the site.
The product is built to learn from a session, store linked memories, recall relevant items later, and let memories fade naturally when they are no longer used. The site presents this as a three-step lifecycle: memory is born, stored and linked, recalled, and then fades.
Yes. The site includes an Enterprise version for team memory sharing, with shared and private memory shown in the interface examples. It is described as a private build and requires contacting the team to get started.
The homepage cites benchmark results on public datasets and mentions 89.4% Recall@5 on LongMemEval in the site description. The site also says the benchmark code lives in the repo, but no separate technical paper is included on the page.
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