# Memory LibSQL

> Use this tool when you need to efficiently manage model context data in memory, solving problems related to data storage and retrieval for MCP servers. It provides a lightweight and fast alternative to traditional disk-based storage, accepting MCP requests as input and returning query results as output. Ideal for use cases requiring low-latency and high-performance data access, such as real-time analytics and machine learning applications.

Canonical page: https://skillsregistry.net/skills/memory-libsql  
JSON: https://api.skillsregistry.net/v1/skills/memory-libsql

## Description

An MCP server implementation that uses LibSQL as a memory store for the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.86
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/memory-libsql)
- **Repository:** <https://github.com/joleyline/mcp-memory-libsql>

## 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": "memory-libsql"
    }
  }
}
```

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