# MCP Memory

> Use this tool when you need to efficiently manage and search large amounts of data across multiple sources, including uploaded files. It solves problems of data discovery and retrieval in data-rich applications, providing a unified search interface. By leveraging HippoRAG for knowledge graph capabilities, MCP Memory enables fast and accurate search results, making it ideal for use cases that require complex data querying and analysis.

Canonical page: https://skillsregistry.net/skills/ddkang1-mcp-mem  
JSON: https://api.skillsregistry.net/v1/skills/ddkang1-mcp-mem

## Description

An MCP server implementing memory solutions for data-rich applications using HippoRAG for efficient knowledge graph capabilities, enabling search across multiple sources including uploaded files.

## 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:** ai-ml
- **Updated:** 2026-05-05

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/e8906n13st)
- **Repository:** <https://github.com/ddkang1/mcp-mem>

## 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": "ddkang1-mcp-mem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ddkang1-mcp-mem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ddkang1-mcp-mem/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