Memori vs claude-mem
Persistent memory for AI agents compared
Memori and claude-mem both capture agent activity and make useful context available across sessions. Memori focuses on a configurable memory layer for LLM applications, while claude-mem centers on searchable coding-session history and selectively injected context.
Memori: Persist Structured Memory for AI Agents
Memori is LLM-agnostic memory infrastructure that turns agent conversations and execution into structured, persistent state. Its Python and TypeScript SDKs support managed cloud, single-tenant cloud, VPC, and on-premises deployments.
claude-mem: Preserve Agent Context Across Sessions
Claude-Mem captures and summarizes agent activity, then retrieves relevant project history in later sessions. It is for developers who want coding agents to retain useful context instead of starting from scratch each time.
| Memori | claude-mem | |
|---|---|---|
| Language | Python | TypeScript |
| License | — | Apache-2.0 |
| Stars | 17.2k | 95.5k |
| Forks | 3.8k | 8.5k |
| Last analyzed | Oct 19, 2026 | Oct 3, 2026 |
Key differences
- Memori organizes conversations and execution into entity, process, and session memory; claude-mem records session observations, summarizes them, and retrieves relevant history.
- Memori offers Python and TypeScript SDKs and integrations for several models and frameworks; claude-mem is primarily designed for Claude Code and documents other agent integrations.
- Memori supports managed cloud and BYODB options; claude-mem stores session history in a local SQLite database and provides a local worker service.
- Memori lists its license as NOASSERTION while its README states Apache 2.0; claude-mem lists Apache-2.0.
- The supplied repository metadata lists 17.1k stars for Memori and 95.5k for claude-mem; both are unarchived.
Choose Memori if you…
- need a memory layer for Python or TypeScript LLM applications and existing infrastructure.
- want managed cloud or bring-your-own-database options.
- need memory organized around entities, processes, and sessions, with support for multiple LLM providers and frameworks.
Choose claude-mem if you…
- want coding agents to retrieve searchable project history from earlier sessions.
- prefer local SQLite storage with search that combines semantic and keyword retrieval.
- need compact search results before loading full memory details, or configurable context injection and privacy exclusions.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.