This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
I’ve been building MouseBase because I got tired of AI agents forgetting everything between conversations.
The idea is pretty simple. Give AI agents a proper long-term memory that developers can actually plug into without having to build the whole thing from scratch.
MouseBase lets you store, search, inspect, and delete memories through a simple API, with PostgreSQL and pgvector underneath.
It’s still early, and I’m building this as a solo developer, so I’d really love to hear what you think.
If you’re building AI agents, how are you handling memory right now? What’s frustrating about your current setup?
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About MouseBase on Product Hunt
“Persistent memory for you AI agent”
MouseBase was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #59 on the daily leaderboard. Store, search, inspect, and delete long-term memory for AI agents with a simple Python, JavaScript, or REST API backed by PostgreSQL and pgvector.
MouseBase was featured in API (98.6k followers), Developer Tools (519k followers) and Artificial Intelligence (478.1k followers) on Product Hunt. Together, these topics include over 214.1k products, making this a competitive space to launch in.
Who hunted MouseBase?
MouseBase was hunted by lumine8. 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.
Want to see how MouseBase stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
lumine8
Hey everyone!
I’ve been building MouseBase because I got tired of AI agents forgetting everything between conversations.
The idea is pretty simple. Give AI agents a proper long-term memory that developers can actually plug into without having to build the whole thing from scratch.
MouseBase lets you store, search, inspect, and delete memories through a simple API, with PostgreSQL and pgvector underneath.
It’s still early, and I’m building this as a solo developer, so I’d really love to hear what you think.
If you’re building AI agents, how are you handling memory right now? What’s frustrating about your current setup?
Would love to hear your thoughts and feedback.