# edgemem

> Use this tool when you need to maintain persistent team context across sessions, enabling seamless collaboration and knowledge retention. Edgemem solves the problem of lost context between sessions by providing cloud-synced memory files and MCP tools. It takes in team data and outputs a shared, persistent memory space, ideal for use in Claude Code projects that require ongoing team collaboration.

Canonical page: https://skillsregistry.net/skills/anuwatthisuka-edgemem  
JSON: https://api.skillsregistry.net/v1/skills/anuwatthisuka-edgemem

## Description

Filesystem-native agent memory for Claude Code, enabling persistent team context across sessions through cloud-synced memory files and MCP tools.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-06-12

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/gx9xmamk57)
- **Repository:** <https://github.com/AnuwatThisuka/edgemem>

## 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": "anuwatthisuka-edgemem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/anuwatthisuka-edgemem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/anuwatthisuka-edgemem/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