# mcp-memory

> Use this tool when you need to provide persistent structured memory and semantic search capabilities to AI clients. It solves problems related to data storage and retrieval, enabling efficient reindexing and search using local embeddings and LanceDB. Ideal for use cases requiring local data management and querying, with a simple stdio-based interface for input and output.

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

## Description

Local MCP server compatible with any studio-based AI client. Provides persistent structured memory, semantic search and reindexing using local embeddings and LanceDB.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [GitHub](https://github.com/natuleadan/mcp-memory)

## 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": "natuleadan-mcp-memory"
    }
  }
}
```

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