remembra-ai/remembra
by Various
Universal memory layer for AI applications. Self-host in minutes. Open source.
MCP
remembra-ai/remembra
Added 1 June 2026
Overview
Remembra is an open-source universal memory layer for AI applications. It can be self-hosted in minutes, providing a persistent memory backend for AI agents and chatbots.
Best for
Best for
Developers who want a simple, self-hosted memory solution for AI applications
Use cases
- Persisting conversation context across sessions for chatbots
- Sharing memory between multiple AI agents or tools
- Self-hosting a private memory backend for data control
How to use
Install
pip install remembra Tools exposed
store_memoryrecall_memoriesupdate_memoryforget_memorieslist_memoriessearch_entitiesshare_memoryrelationships_atingest_conversationhealth_check
Tested with
Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, ChatGPT
Notes
Remembra is an open-source universal memory layer for AI applications. It can be self-hosted in minutes, providing a persistent memory backend for AI agents and chatbots.
13 stars on GitHub. Last updated 2026-04-30. Licensed MIT.
Use cases
- Persisting conversation context across sessions for chatbots
- Sharing memory between multiple AI agents or tools
- Self-hosting a private memory backend for data control
Pros
- Open-source and self-hosted for full data ownership
- Quick setup with minimal configuration
- Designed as a universal drop-in memory layer
Cons
- Very small community (13 GitHub stars) indicating early stage
- Limited ecosystem and third-party integrations
- Potential lack of documentation and support
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Open-source and self-hosted for full data ownership
- Quick setup with minimal configuration
- Designed as a universal drop-in memory layer
Cons
- Very small community (13 GitHub stars) indicating early stage
- Limited ecosystem and third-party integrations
- Potential lack of documentation and support
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
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