pulsemcp verified Safe content atomic mcp-remote

Video Editor (FFMpeg)

This video editing MCP server, developed by Kush Agrawal, enables AI assistants to perform a wide range of video editing operations using FFmpeg. Built with Python and leveraging the MCP framework, it provides a single powerful tool, 'execute_ffmpeg', which validates and executes FFmpeg commands with real-time progress tracking. The server supports operations like trimming, merging, format conversion, speed adjustment, audio manipulation, and subtitle addition. By abstracting complex FFmpeg operations into a natural language interface, it allows AI systems to easily manipulate video content. This implementation is particularly useful for automating video editing tasks, content creation, and media processing workflows, making it suitable for applications in video production, social media content generation, and automated video analysis.

Cognium trust score

99%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.

Scan details: Circle-IR · 2026-09-19 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: social-media
Source: PulseMCP
Repository: github.com/kush36agrawal/video_editor_mcp
Author type: human
Last scanned: 2026-09-19
Updated: 2026-09-19

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MCP

Resolve Video Editor (FFMpeg) from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"