# memcp

> Use this tool when you need to store and retrieve knowledge across sessions without consuming context window tokens. It solves the problem of knowledge persistence and organization, allowing for efficient recall of information. The memcp tool takes in knowledge inputs and outputs organized and retrievable data, making it ideal for use cases where session-to-session memory is required.

Canonical page: https://skillsregistry.net/skills/maydali28-memcp  
JSON: https://api.skillsregistry.net/v1/skills/maydali28-memcp

## Description

Persistent memory MCP server that allows Claude to store, organize, and retrieve knowledge across sessions without consuming context window tokens.

## Trust

- **Trust score (0–1):** 0.41
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/coopzdzbaw)
- **Repository:** <https://github.com/maydali28/memcp>

## 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": "maydali28-memcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/maydali28-memcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/maydali28-memcp/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