Memori vs plur
Persistent memory for AI agents compared
Memori and plur both give AI agents persistent memory that can carry useful context across sessions and tools. Memori focuses on structured memory for LLM applications with cloud or bring-your-own-database options, while plur stores readable YAML locally and supports sharing through Git.
Memori: Give AI Agents Persistent Memory
Memori adds persistent, structured memory to LLM applications and agents, capturing conversations and execution context for later recall. It suits teams building stateful agents who want a memory layer that works across models and existing infrastructure.
plur: Share Persistent Memory Across AI Agents
PLUR gives AI agents a shared, local-first memory store of readable YAML files. It suits developers who want corrections and project conventions to carry across sessions and tools without relying on a hosted memory service.
| Memori | plur | |
|---|---|---|
| Language | Python | TypeScript |
| License | NOASSERTION | Apache-2.0 |
| Stars | 17.1k | 298 |
| Forks | 3.6k | 36 |
| Last analyzed | Oct 3, 2026 | Oct 10, 2026 |
Key differences
- Memori structures memory around attributes, events, facts, people, preferences, relationships, rules, and skills; plur stores engrams and timestamped episodes in YAML files.
- Memori offers managed Memori Cloud or a bring-your-own-database option; plur is local-first and can sync memory across devices or teams using Git.
- Memori provides Python and TypeScript SDKs and integrations for LLMs and agent frameworks; plur is written in TypeScript and connects agent environments through MCP and dedicated integrations.
- Memori's supplied license field is NOASSERTION, while its README states Apache 2.0; plur is listed as Apache-2.0 licensed.
- Memori has 17.1k stars and 3.6k forks; plur has 298 stars and 36 forks.
- Memori targets production LLM applications and agents broadly; plur emphasizes developers using coding agents and inspectable, portable memory.
Choose Memori if you…
- need structured memory for LLM applications and production agents.
- want Python and TypeScript SDKs, framework integrations, and cloud or database deployment options.
- need to preserve execution context and attribute memories by entity and process.
Choose plur if you…
- want readable YAML memory stored locally and directly inspectable or editable.
- need the same project knowledge across supported coding agents, with optional Git-based sharing.
- want keyword and embedding-based local search, plus a timeline of agent events.
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.