# agent-memex

> agent-memex — gudmundur76-agent-memex. Use this tool when you need to augment AI agents with persistent memory, enabling them to store and semantically search memories. The agent-memex provides a memory layer that solves the problem of knowledge retention and recall, allowing agents to learn from past experiences. It accepts inputs via MCP or REST and outputs relevant memories, making it ideal for use cases requiring long-term memory and information retrieval.

Canonical page: https://skillsregistry.net/skills/gudmundur76-agent-memex  
JSON: https://api.skillsregistry.net/v1/skills/gudmundur76-agent-memex

## Description

Free, persistent memory layer for AI agents, enabling storage and semantic search of memories via MCP or REST.

## Trust

- **Trust score (0–1):** 0.58
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/deadlr0z02)
- **Repository:** <https://github.com/Gudmundur76/agent-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": "gudmundur76-agent-memex"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gudmundur76-agent-memex` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gudmundur76-agent-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