# Memvid

> Use this tool when you need to enable AI agents to store and retrieve information across sessions, or build knowledge bases from accumulated interactions. Memvid provides persistent memory capabilities through file-based storage, allowing agents to create isolated memory files and perform semantic searches. It is ideal for applications that require context maintenance, conversation history, or knowledge base construction, with optional natural language query features for advanced information retrieval.

Canonical page: https://skillsregistry.net/skills/khgs2411-memvid  
JSON: https://api.skillsregistry.net/v1/skills/khgs2411-memvid

## Description

This MCP server provides persistent, file-based memory capabilities for AI agents through integration with the Memvid SDK. It enables project-based memory management where agents can create isolated memory files (.mv2), store text documents with metadata, and perform hybrid semantic/lexical search across stored content. The implementation includes an optional natural language query feature that requires an OpenAI API key, allowing agents to ask questions about their stored memories. Built with TypeScript and Bun, it supports both local and home directory storage options, making it useful for applications that need to maintain context across sessions, remember previous conversations, or build knowledge bases from accumulated interactions.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/khgs2411-memvid)
- **Repository:** <https://github.com/khgs2411/memvid_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": "khgs2411-memvid"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/khgs2411-memvid` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/khgs2411-memvid/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