# memcp

> Use this tool when you need to retain information across conversations, enabling AI assistants to recall context and maintain continuity. It solves problems of data loss and context switching, allowing for more cohesive and personalized interactions. With a simple interface for storing and retrieving data, memcp takes in conversation data as input and outputs relevant information from its local SQLite database.

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

## Description

Provides persistent memory for AI assistants like Claude, storing and retrieving information across conversations using a local SQLite database.

## 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:** database
- **Updated:** 2026-05-26

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/w3ezi2xzbs)
- **Repository:** <https://github.com/moshez/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": "moshez-memcp"
    }
  }
}
```

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