# WorkingMemory

> WorkingMemory — ai-workingmemory-memory. Use this tool when you need to retain and retrieve information across multiple interactions and clients, solving problems of knowledge loss and inconsistent responses. WorkingMemory provides a persistent personal memory for AI assistants, allowing them to save, search, and recall data seamlessly. It takes in user inputs and AI-generated data as inputs and outputs relevant information to inform responses and actions.

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

## Description

Persistent personal memory for AI assistants — save, search, and recall across every MCP client.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

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

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.workingmemory%2Fmemory)

## Use it

MCP endpoint published by the skill: `https://app.workingmemory.ai/mcp`

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": "ai-workingmemory-memory"
    }
  }
}
```

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