memora

Give your AI agents persistent, collective memory, with deduplicating absorb, supersession lineage, semantic search, and a graph UI. Speaks MCP.

Not yet testedsource: GitHubPythonMITcommit c5624e8303f0

Python, MIT licensed. The project labels itself: agent memory, ai agent, claude, claude code, cloudflare d1, codex, knowledge graph and llms.

memora has not been verified yet.

Measured by Argusic on a fresh machine every time. Every number links to its evidence.

At a glance

verdict
Not yet tested
Argusic Score
not scored yet
recorded runs
0
last tested
-
stars
731
forks
78
open issues
3
watchers
5
size
104 MB
created
last push

Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.

Also tested, in the same area

Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.

Run history

No recorded runs.

Topics (from GitHub)

agent-memoryai-agentclaudeclaude-codecloudflare-d1codexknowledge-graphllmsmcpmcp-servermemorymodel-context-protocolragsemantic-searchsemantic-search-algorithmsqlite

Embed the badge

Markdown for the project README. It links back here; terms on the terms page.

[![Tested by Argusic](https://argusic.com/badge/memora.svg)](https://argusic.com/subject/memora)

Questions

Does memora run?
memora has not been fully verified yet. No recorded run has produced a verdict yet.
How did Argusic test memora?
On a fresh, disposable machine, with every command recorded. 0 attempts are recorded, and the full method is on the methodology page.
Where is the evidence for memora?
All 0 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.

Discussion