# Memory MCP

> Use this tool when you need to retain information across multiple conversations, enabling AI agents to recall previous interactions and maintain context. The Memory MCP solves problems of knowledge loss and inconsistency, providing a persistent storage solution for conversational data. It accepts input from conversation transcripts and outputs relevant information to inform subsequent interactions.

Canonical page: https://skillsregistry.net/skills/hamzafarhan-memory  
JSON: https://api.skillsregistry.net/v1/skills/hamzafarhan-memory

## Description

A knowledge-graph-based memory system for AI agents that enables persistent information storage between conversations.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

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

## 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": "hamzafarhan-memory"
    }
  }
}
```

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