# memmd-mcp

> Use this tool when you need to synchronize shared memory across multiple AI agents and interfaces, such as Claude Desktop, Cursor, and OpenAI Codex, to enable seamless collaboration and data sharing. It solves problems of data inconsistency and fragmentation by providing a unified memory layer, allowing for efficient information exchange and updates. This tool is ideal for use cases requiring real-time data synchronization and access across various AI-powered applications and clients.

Canonical page: https://skillsregistry.net/skills/matamong-memmd-mcp  
JSON: https://api.skillsregistry.net/v1/skills/matamong-memmd-mcp

## Description

A shared memory layer for AI agents — one memory.md synced across Claude Desktop, Cursor, Claude Code, OpenAI Codex, and any MCP client.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/g0w3nhqrju)
- **Repository:** <https://github.com/matamong/memmd-mcp>

## 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": "matamong-memmd-mcp"
    }
  }
}
```

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