# memvid-mcp-server

> Use this tool when you need to encode text data into videos for efficient semantic search, solving problems of slow and inaccurate text-based search methods. It takes in text data as input and outputs encoded video files, enabling fast and accurate search capabilities. Ideal for applications requiring rapid information retrieval, such as data analysis, research, and knowledge management.

Canonical page: https://skillsregistry.net/skills/ferrants-memvid-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/ferrants-memvid-mcp-server

## Description

Encodes text data into videos for fast semantic search using memvid.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/o4kz67hrgo)
- **Repository:** <https://github.com/ferrants/memvid-mcp-server>

## 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": "ferrants-memvid-mcp-server"
    }
  }
}
```

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