# AI Long-Term Memory MCP Server

> Use this tool when you need to enable AI agents to retain information across sessions and recall relevant knowledge through semantic search. It solves the problem of ephemeral memory in AI systems, allowing them to learn and adapt over time. With layered memory architecture and automatic context-aware retrieval, it provides a persistent and accessible long-term memory interface for AI agents.

Canonical page: https://skillsregistry.net/skills/hpy6370-sys-memory-mcp  
JSON: https://api.skillsregistry.net/v1/skills/hpy6370-sys-memory-mcp

## Description

Provides persistent long-term memory for AI agents with semantic search and activation-based decay. Enables AI systems to remember across sessions through layered memory architecture and automatic context-aware retrieval.

## Trust

- **Trust score (0–1):** 0.17
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/uqhou1csnz)
- **Repository:** <https://github.com/hpy6370-sys/memory-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "hpy6370-sys-memory-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hpy6370-sys-memory-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hpy6370-sys-memory-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt