# mememory

> mememory — scott-walker-mememory. Use this tool when you need to store and manage persistent semantic memory for AI agents, enabling them to retain and recall knowledge over time. It solves problems of data loss and inconsistency by providing a local, PostgreSQL-based repository with vector search capabilities. Ideal for use cases requiring robust, self-contained knowledge management, with inputs including data to be stored and retrieved, and outputs comprising recalled information and insights.

Canonical page: https://skillsregistry.net/skills/scott-walker-mememory  
JSON: https://api.skillsregistry.net/v1/skills/scott-walker-mememory

## Description

Persistent semantic memory for AI agents. MCP server with PostgreSQL + pgvector. All data stays local.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** database
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/scott-walker/mememory)

## 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": "scott-walker-mememory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/scott-walker-mememory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/scott-walker-mememory/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