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Alaya Memory Engine MCP Server

@SecurityRonin

Repository

Basic information

Category

Memory & Knowledge

Transports

stdio

Author

SecurityRonin

Submitted by

Albert Hui

About Alaya Memory Engine MCP Server

A local memory engine for AI agents. Stores conversation episodes, consolidates knowledge through a neuroscience-inspired lifecycle, and builds a personal knowledge graph with emergent categories, preferences, and semantic recall. Local SQLite, zero config, 10 MCP tools.

#memory#knowledge-graph#mcp#mcp-server#ai#agent#sqlite#local

Alaya Memory Engine MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "alaya": {
      "command": "npx",
      "args": [
        "-y",
        "alaya-mcp"
      ]
    }
  }
}

Alaya Memory Engine MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is Alaya Memory Engine?

Alaya Memory Engine is a local memory server for AI agents. It stores conversation episodes, consolidates knowledge through a neuroscience-inspired lifecycle (strengthening, transformation, forgetting), and builds a personal knowledge graph with emergent categories, preferences, and semantic recall. It is designed for developers who want their AI agents to have persistent, evolving memory.

How to use Alaya Memory Engine?

Install the server via npx alaya-memory-engine (zero configuration required) and configure your MCP client to connect to it. The server exposes 10 MCP tools: remember, recall, learn, status, knowledge, preferences, categories, neighbors, maintain, and purge.

Key features of Alaya Memory Engine

  • Stores conversation episodes for long-term memory
  • Consolidates knowledge via strengthening, transformation, and forgetting
  • Builds a personal knowledge graph from interactions
  • Discovers emergent categories, preferences, and semantic recall
  • Runs fully local with SQLite and no external configuration
  • Provides 10 dedicated MCP tools for memory management

Use cases of Alaya Memory Engine

  • Giving conversational AI agents persistent, personalized memory
  • Building a self‑updating knowledge base from user interactions
  • Learning and adapting to user preferences over time
  • Enabling semantic recall of past episodes and relationships

Frequently asked questions

1

What tools does Alaya Memory Engine provide?

It provides 10 MCP tools: `remember`, `recall`, `learn`, `status`, `knowledge`, `preferences`, `categories`, `neighbors`, `maintain`, and `purge`.

2

Does Alaya Memory Engine require a cloud service or external API?

No. It runs entirely locally using SQLite with zero configuration. No external services or API keys are needed.

3

How is knowledge organized and retrieved?

Knowledge is stored as a personal knowledge graph with emergent categories, preferences, and semantic recall. The `recall` tool retrieves relevant memories based on the learned graph structure.

4

What makes Alaya Memory Engine different from a simple database or file storage?

It uses a neuroscience‑inspired lifecycle that strengthens important memories, transforms related knowledge, and forgets irrelevant information over time, mimicking human memory processes rather than simple storage.

Comments

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