# memex

> Use this tool when you need to access and manage a centralized memory system for Large Language Models (LLMs), enabling persistent recall and validation of information. It solves problems related to knowledge retention and integration with upstream servers, providing a gateway for seamless data exchange. The memex tool accepts input from LLMs and outputs validated information, making it ideal for applications requiring reliable memory recall and MCP server integration.

Canonical page: https://skillsregistry.net/skills/queflyhq-memex  
JSON: https://api.skillsregistry.net/v1/skills/queflyhq-memex

## Description

Centralized agentic memory and MCP gateway for LLMs, enabling persistent memory recall, validation, and integration with upstream MCP servers.

## Trust

- **Trust score (0–1):** 0.80
- **Verification tier:** verified
- **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/sa8eoegtt4)
- **Repository:** <https://github.com/askmohanty/memex>

## 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": "queflyhq-memex"
    }
  }
}
```

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