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Memgar
memory guard for AI agents
Open-source memory poisoning defense for AI agents — detect, sanitize, quarantine, and block unsafe memory before it influences an agent.
Hi HN, I built Memgar, an open-source memory layer for AI agents.
The goal is to let agents persist, retrieve, and version useful context across runs instead of starting from scratch every session. It is intended for local/dev workflows where memory needs to be inspectable and controllable.
I would appreciate feedback on the design, API, and whether the Git-like approach to agent memory makes sense.
Yours comments and contributions would make me happy.
About Memgar on Product Hunt
“memory guard for AI agents”
Memgar was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #138 on the daily leaderboard. Open-source memory poisoning defense for AI agents — detect, sanitize, quarantine, and block unsafe memory before it influences an agent.
On the analytics side, Memgar competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Memgar performed against the three products that launched closest to it on the same day.
Who hunted Memgar?
Memgar was hunted by memgar. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Memgar including community comment highlights and product details, visit the product overview.
memgar