# memory-mesh

> memory-mesh — das-chinmay-memory-mesh. Use this tool when you need to enable shared memory and collaboration between AI models like Claude, ChatGPT, and Gemini, with built-in conflict detection to ensure data consistency. The memory-mesh server provides a local-first approach, allowing for seamless integration and synchronization of data. It accepts git inputs and offers a unified interface for AI models to access and update shared memory.

Canonical page: https://skillsregistry.net/skills/das-chinmay-memory-mesh  
JSON: https://api.skillsregistry.net/v1/skills/das-chinmay-memory-mesh

## Description

🧠 Local-first MCP server giving Claude, ChatGPT and Gemini shared memory with conflict detection

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-06-18

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/Das-Chinmay/memory-mesh)

## 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": "das-chinmay-memory-mesh"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/das-chinmay-memory-mesh` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/das-chinmay-memory-mesh/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