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SecurityRonin/alaya

by Various

A memory engine for conversational AI agents, inspired by neuroscience and Buddhist psychology

S

MCP

SecurityRonin/alaya

Added 1 June 2026

#ai #ai-agent-tools #memory #neurosciences #yogacara

Overview

SecurityRonin/alaya is a memory engine for conversational AI agents, implemented in Rust. It is inspired by principles from neuroscience and Buddhist psychology to manage agent memory. The tool provides a framework for storing and recalling contextual information across interactions.

Best for

Best for
Developers building conversational agents that need sustained context over extended interactions

Use cases

  • Building conversational agents with persistent long-term memory
  • Creating AI systems that recall past user interactions
  • Developing context-aware responses in dialogue agents

How to use

Install

pip install alaya-memory

Tools exposed

  • node_category
  • import_claude_mem
  • import_claude_code
  • ALAYA_DB
  • ALAYA_LLM_API_KEY
  • ALAYA_LLM_API_URL
  • ALAYA_LLM_MODEL

Tested with

Claude Desktop, Claude Code, Cursor, Cline, ChatGPT

Notes

SecurityRonin/alaya is a memory engine for conversational AI agents, implemented in Rust. It is inspired by principles from neuroscience and Buddhist psychology to manage agent memory. The tool provides a framework for storing and recalling contextual information across interactions.

12 stars on GitHub. Last updated 2026-04-20. Licensed MIT.

Use cases

  • Building conversational agents with persistent long-term memory
  • Creating AI systems that recall past user interactions
  • Developing context-aware responses in dialogue agents

Pros

  • Performant due to Rust implementation
  • Unique conceptual foundation for memory management
  • Open source for customization and integration

Cons

  • Low community adoption with only 12 GitHub stars
  • Limited documentation and ecosystem support
  • Unconventional philosophical basis may require deeper understanding

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Performant due to Rust implementation
  • Unique conceptual foundation for memory management
  • Open source for customization and integration

Cons

  • Low community adoption with only 12 GitHub stars
  • Limited documentation and ecosystem support
  • Unconventional philosophical basis may require deeper understanding
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