# localmem-mcp

> localmem-mcp — openagenthq-localmem-mcp. Use this tool when you need to enable AI agents to retain information across sessions without relying on cloud services. It solves problems of data persistence and semantic search by providing a local-first memory solution using SQLite and on-device embeddings. This tool is ideal for use cases requiring offline access, data privacy, and efficient recall of learned information.

Canonical page: https://skillsregistry.net/skills/openagenthq-localmem-mcp  
JSON: https://api.skillsregistry.net/v1/skills/openagenthq-localmem-mcp

## Description

Gives AI agents persistent, local-first memory using SQLite and on-device embeddings, enabling semantic search and recall across sessions with no cloud calls.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/jltzktadoc)
- **Repository:** <https://github.com/OpenAgentHQ/localmem-mcp>

## 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": "openagenthq-localmem-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/openagenthq-localmem-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/openagenthq-localmem-mcp/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