# ai.atlaso/mcp

> ai.atlaso/mcp — ai-atlaso-mcp. Use this tool when you need to unify and persist data across multiple AI applications, enabling seamless information sharing and retrieval. It solves problems of data fragmentation and inconsistency by providing a shared memory layer, accepting inputs from various AI tools and outputting unified data for efficient processing. Ideal for use cases requiring centralized data management and cross-tool collaboration.

Canonical page: https://skillsregistry.net/skills/ai-atlaso-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ai-atlaso-mcp

## Description

AI memory layer — one shared, persistent memory across every AI tool you connect.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.atlaso%2Fmcp)
- **Repository:** <https://github.com/atlaso-labs/mcp>

## Use it

MCP endpoint published by the skill: `https://mcp.atlaso.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-atlaso-mcp"
    }
  }
}
```

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