Item detail

MemoriLabs/Memori

Memori MemoriLabs/Memori is an Apache-2.0 open-source LLM-agnostic agent-native memory infrastructure layer that gives any agent (Claude Code, Codex, custom Python agents, LangChain, etc.) persistent, queryable, and portable memory without forcing a specific framework, with first-class support for short-term working memory, long-term semantic memory, and shared memory across agents and sessions.

Score8.3
Popularity15347.0
Risklow
TierGold
Score breakdown
Usefulness8.7
Novelty10.0
Momentum10.0
Maturity9.0
Open-source/build7.4
Evidence7.2
Workflow potential9.4
Setup ease6.5

Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.

Why it matters

Useful for AI engineers, agent builders, and platform teams who want their agents to remember user preferences, prior task outcomes, and cross-session context without bolting on a vector DB + custom glue code per project, because Memori MemoriLabs/Memori from MemoriLabs ships an LLM-agnostic memory layer with short-term working memory, long-term semantic memory, and shared cross-agent memory in on

Who should use it

BuildersPower users

Who should skip it

Skip if the source link, docs, or setup requirements do not match your workflow.

Risk explanation

Risk label needs manual review.

Evidence links

Closest alternatives / related signals