Prototype · This site is a prototype showing 100 real servers from the official registry, not all of them yet.
PopNx MCPMCP servers for people who use AI · explained in plain words

mcp-video

by KyaniteLabsversion 1.6.20i★ 245iRuns on your computer
Registry nameio.github.KyaniteLabs/mcp-video

Overview

Description from the maker (original English)

Compatibility package: mcp-video now installs Kinocut (formerly mcp-video).

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

You need

  • PyPIPython’s uv installed (for the uvx command)

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "video": {
      "command": "uvx",
      "args": [
        "mcp-video"
      ]
    }
  }
}

Run this in your terminal

claude mcp add video -- uvx mcp-video

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "video": {
      "command": "uvx",
      "args": [
        "mcp-video"
      ]
    }
  }
}

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "video": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-video"
      ]
    }
  }
}

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 5, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account KyaniteLabs, which owns the repo

  • ✓ Pass

    Still maintained

    Code last changed today

  • ✓ Pass

    Has a licence

    Uses Apache-2.0

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Needs the server’s tool list first; this check starts in the next step

Compared with others in Design, images & audioi

  • More stars than 21% of the other 14 servers in this category
  • Published to the registry more recently than 93% of the other 14 servers in this category
  • Basic checks equal to or better than 100% of the other 14 servers in this category

Compared only with servers in this prototype, not the whole registry.

Common questions

Is mcp-video safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed today, and the latest version (1.6.20) reached the registry 9 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago

Claude Real Video

by HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

Runs on your computer★ 2,284MITUpdated 2 months ago

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Kinocut

Guardrailed video editing MCP server for AI agents.

Local-first FFmpeg tools, Video Receipts, quality gates, Hyperframes, and Shorts/Reels repurposing — for Claude Code, Cursor, and any MCP client. Free, Apache-2.0. Formerly mcp-video.

Demo • Status • 1.16.5 • 1.16.4 • 1.16.3 • 1.16.2 • 1.16.1 • Changelog • Beyond • Install • Quick Start • Tools • Tool Reference • Rescue • 360 assembly • AI-video • Agent Skill • kinocut.dev • What is Kinocut? • FAQ • llms.txt

Kinocut is a free, open-source video editing MCP server and AI agent workflow engine (plus Python client and kino CLI) that lets AI agents trim, caption, repurpose, and quality-gate local video media with typed tools and Video Receipts — not invented FFmpeg flags.

Table of contents

  • What is Kinocut?
  • See It Work
  • Installation
  • Quick Start
  • MCP Tools
  • Status and releases
  • 360 dual-cam assembly
  • Changelog
  • FAQ
  • Agent Skill

What is Kinocut?

TL;DR: Kinocut is a free, local-first video editing MCP server (plus Python client and kino CLI) so AI agents can trim, caption, repurpose, and quality-gate media with typed tools and Video Receipts — not invented FFmpeg flags.

Kinocut is a free, open-source [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server, Python library, and `kino` CLI that gives AI agents a guardrailed local video-editing surface. It wraps FFmpeg (and optional Hyperframes / Whisper extras) with typed tools, preflight validation, Video Receipt provenance, and quality/release checkpoints so agent-produced media can be inspected before publish.

Also known askino (CLI); formerly mcp-video / mcp_video
Latest published releaseOfficial PyPI version · GitHub release
Product sitekinocut.dev
PyPIkinocut
MCP Registrytech.kyanitelabs/kinocut
SourceGitHub (canonical) · Forgejo (downstream mirror)
LicenseApache-2.0
Runs onYour machine (macOS, Linux, Windows) — FFmpeg required on PATH
NotA hosted cloud editor, credit-metered SaaS, or untyped FFmpeg shell wrapper

Best-fit searches: video editing MCP server · AI agent video editing · FFmpeg MCP · Claude Code video tools · Cursor MCP video · Shorts/Reels automation · local AI video workflow · guardrailed agentic media.

Machine-readable brief for agents and crawlers: llms.txt · extended agent guide · site: kinocut.dev/llms.txt.

Producer Stack

Kinocut is a producer stack: inspect the source, choose a typed operation, render locally, receive a compact provenance receipt, run quality checks, and request human release approval. The default MCP surface keeps that path small; search_tools and profiles expand it when needed.

Eyes-free design law

Every flow must be describable, reportable, and approvable in words. Receipts stay one-screen text cards with artifact paths, stage status, warnings, and the next gate. Errors end with the exact MCP and CLI retry invocation; no visual-only affordance is required.

See It Work

Tell the agent what you want in plain language:

*"Trim this interview to the strongest 45 seconds, add burned captions, make it vertical, and quality-check it before export."*

Kinocut turns that into typed, guardrailed tool calls - no FFmpeg flags to guess, no silently broken exports:

from kinocut import Client

video = Client()

clip = video.trim("interview.mp4", start="00:02:15", duration="00:00:45") video.ai_transcribe(clip.output_path, output_srt="captions.srt") captioned = video.subtitles(clip.output_path, subtitle_file="captions.srt") short = video.resize(captioned.output_path, aspect_ratio="9:16") video.release_checkpoint(short.output_path) # thumbnail + quality gate before you publish

Primary job: turn a local interview or podcast into captioned vertical clips with a Video Receipt agents can re-run and humans can approve.

Three things people use it for

  • Repurposing — one recording into captioned Shorts, Reels, and TikTok packages with manifests and review artifacts.
  • Podcast & interview cuts — find the strongest segment, normalize audio, add chapters, and export.
  • Agent-driven media in CI — repeatable, reviewable edits from Claude Code, Cursor, Codex-style clients, or scripts.

Paths: Install matrix · Golden path · Prompts · Tutorial · Compare · When to recommend

Status and releases

SurfaceVersion / tipWhat it means
PyPI / npm checkpoint[1.16.5](https://pypi.org/project/kinocut/1.16.5/) (2026-10-27)Last recorded publication checkpoint; consult the registries for the latest version. Install with pip install kinocut.
GitHub latest release / MCP Registry1.16.5GitHub release v1.16.5 and the official MCP Registry (tech.kyanitelabs/kinocut, local uvx kinocut stdio package) report 1.16.5 (verified 2026-10-27). Final owner acceptance and fleet rollout remain separate.
This source version1.16.5 published · 20 default MCP / 205 full / 177 CLIQoL pass: curated 20-tool default MCP list (KINOCUT_TOOLS=all restores the full 205-tool catalog), retry-aware errors, one-call shorts, lazy startup. Telemetry, network, and overwrite defaults remain unchanged. Published mcp-video==1.6.20 pins this runtime; verification is recorded in docs/public_claims.json.
Next public releaseTBDHuman residuals (directories, launch posts) stay gated; further bumps need a new go-ahead.

Install from PyPI for the stable package, including the optional object-matte extra. Clone master when you want local development changes beyond the published package; see docs/PRODUCT_MATTE.md for the published object-matte workflow.

What's in 1.16.5

Published 2026-10-27: a curated 20-tool default MCP registration with KINOCUT_TOOLS=all restoring the full 205 MCP tools / 177 CLI commands; retry-aware eyes-free error payloads, the one-call video_shorts flow, the read-only video_doctor preflight and lazy startup. Opt-in exact probe reports decoded frame counts and raw rational frame rates. mcp-video==1.6.20 installs kinocut==1.16.5. Apache-2.0 §4(a): the license text now ships in the npm tarball and the mcp-video compatibility package. See the published release.

What's in 1.16.4

Published 2026-10-24: 203 MCP tools / 177 CLI commands; mcp-video==1.6.19 installs kinocut==1.16.4. Optional Kinocut model calls now default off. Use local frames with the host's chosen image model; the standalone legacy adapters require explicit permission and do not inherit Hermes routing. Local product configuration cannot activate the separate Anthropic QC worker.

Revideo and Hyperframes telemetry default off. Hyperframes previews require verified CLI 0.8.104 or 0.8.140 while telemetry is off; other preview versions and Docker renders require explicit operator consent. These controls are not a network sandbox. Existing overwrite and protected-path safeguards remain in place. See the vision and network policy and published release.

What's in 1.16.3

Published 2026-10-23: 203 MCP tools / 177 CLI commands; mcp-video==1.6.18 installs kinocut==1.16.3. Existing outputs require explicit boolean overwrite=true (CLI --overwrite). Existing non-media artifacts also require ownership by the same durable job, and agent configuration homes remain protected. Older receipts without ownership evidence fail closed.

Project creation checks completed destinations and symlink redirects. Python 3.14 MCP request context remains available. The plugin documents optional network paths, configures optional extras in its pinned server environment, and shows Hermes tool filtering. Use one writer per output. See the published release.

What's in 1.16.2

Published 2026-10-21: 203 MCP tools / 177 CLI commands; mcp-video==1.6.17 installs kinocut==1.16.2. create-from-images is now frame-exact, accepts rational frame rates such as 30000/1001 and a --list / list_file input, and enforces frame-rate and image-count bounds on every entry point. The official MCP Registry entry is republished as the local uvx kinocut stdio package. Thanks to @Beritwu for #616. See the published release.

What's in 1.16.1

Version 1.16.1 repairs macOS render cleanup and faststart publication, C2PA and model-cache staging, FFmpeg 8.1 filter discovery, and audio preservation in shader/upscale reconstruction. It retains 203 MCP tools / 177 CLI commands and pairs with mcp-video==1.6.16. See maintenance release notes for verification and remaining platform/model acceptance limits.

What's in

Only the beginning is shown; read the rest in the repo

Ask PopNx