Remembrane – agent memory in one SQLite file, zero dependencies
This is a small library for giving an agent persistent memory without running any infrastructure. The whole store is one SQLite file, and the default install has no dependencies. I built it because whenever I wanted an agent to remember a handful of facts across sessions, the options were a hosted API, a vector database, or a framework, and that felt like too much for what is usually a few thousand short strings. The part I find most useful is that recall is deterministic, so you can write unit tests that assert what your agent remembers and run them in CI. I haven't seen that elsewhere and…
Remembrane – agent memory in one SQLite file, zero dependencies launched on August 7, 2026 with 13 votes, #880 of 23,274 launches that month and more than 90% of that year's launches.
In plain words
Remembrane is a library that gives AI agents persistent memory stored in a single SQLite file with no external dependencies. It's designed for developers who need agents to retain facts across sessions without running hosted services or vector databases. Key features include deterministic recall for reliable unit testing, transparent scoring for search results, and a complete journal of all changes for snapshots and diffs.
written from the facts on this page · September 2026
From the sources
Local-first memory for AI agents: one SQLite file, zero deps. Recency-aware exact recall, conflict detection, time-travel journal, MCP server. - satyasairay/remembrane
In the maker’s words, at launch
This is a small library for giving an agent persistent memory without running any infrastructure. The whole store is one SQLite file, and the default install has no dependencies. I built it because whenever I wanted an agent to remember a handful of facts across sessions, the options were a hosted API, a vector…
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