# Memory MCP

> Use this tool when you need to efficiently manage and retrieve persistent memory data with advanced filtering and search capabilities. It solves problems related to data organization, retrieval, and tracking, particularly in scenarios where dependencies may fail. The Memory MCP server accepts metadata and vector data as inputs and provides filtered search results as outputs, making it ideal for use cases requiring robust and fault-tolerant data management.

Canonical page: https://skillsregistry.net/skills/tungvt93-memory-mcp  
JSON: https://api.skillsregistry.net/v1/skills/tungvt93-memory-mcp

## Description

A local-first MCP server for persistent memory with vector search, metadata filtering, fact tracking, and graceful degradation when dependencies fail.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/qr4cjp10qk)
- **Repository:** <https://github.com/tungvt93/Memory-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": "tungvt93-memory-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tungvt93-memory-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tungvt93-memory-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