# Media Editor

> Use this tool when you need to edit media files, such as trimming videos or transcribing audio, and require a robust server-based solution. The Media Editor solves problems related to media post-production, content creation, and automation, accepting input files and producing edited outputs with customizable options. It is ideal for use cases involving large-scale media processing, requiring inputs like video files and outputting trimmed clips, transcripts, or themed thumbnails.

Canonical page: https://skillsregistry.net/skills/wmeints-media-editor  
JSON: https://api.skillsregistry.net/v1/skills/wmeints-media-editor

## Description

An MCP server that provides media editing tools powered by FFmpeg. It enables video trimming to specific time ranges, audio transcription using NVIDIA NeMo technology, and generation of themed thumbnails with customizable title cards. The server includes a doctor command to verify FFmpeg installation and requires Python 3.12+, the uv package manager, and NVIDIA GPU with CUDA support for transcription features.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **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:** [PulseMCP](https://www.pulsemcp.com/servers/wmeints-media-editor)
- **Repository:** <https://github.com/wmeints/media-editor>

## 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": "wmeints-media-editor"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/wmeints-media-editor` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/wmeints-media-editor/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