Maintainer of this skill?
Automated security scan — not a certification.
by KyaniteLabs
Guardrailed video editing MCP server for AI agents. FFmpeg, Hyperframes, repurposing tools, Python client, and CLI. Local, fast, free.
# Add to your Claude Code skills
git clone https://github.com/KyaniteLabs/kinocutGuides for using ai agents skills like kinocut.
Last scanned: 8/6/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-08-06T06:30:48.757Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how kinocut compares with popular alternatives.
kinocut is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by KyaniteLabs. Guardrailed video editing MCP server for AI agents. FFmpeg, Hyperframes, repurposing tools, Python client, and CLI. Local, fast, free. It has 242 GitHub stars.
Yes. kinocut passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/KyaniteLabs/kinocut" and add it to your Claude Code skills directory (see the Installation section above).
kinocut is primarily written in Python. It is open-source under KyaniteLabs on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh kinocut against similar tools.
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Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
Kinocut is a free, open-source video editing MCP server and AI agent workflow engine (plus Python client and
kinoCLI) that lets AI agents trim, caption, repurpose, and quality-gate local video media with typed tools and Video Receipts — not invented FFmpeg flags.
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) 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 as | kino (CLI); formerly mcp-video / mcp_video |
| Latest published release | Official PyPI version · GitHub release |
| Product site | kinocut.dev |
| PyPI | kinocut |
| MCP Registry | tech.kyanitelabs/kinocut |
| Source | GitHub (canonical) · Forgejo (downstream mirror) |
| License | Apache-2.0 |
| Runs on | Your machine (macOS, Linux, Windows) — FFmpeg required on PATH |
| Not | A 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.
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.
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.
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
Paths: Install matrix · Golden path · Prompts · Tutorial · Compare · When to recommend
| Surface | Version / tip | What it means |
|---|---|---|
| PyPI / npm checkpoint | 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 Registry | 1.16.5 | GitHub 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 version | 1.16.5 published · 20 default MCP / 205 full / 177 CLI | QoL 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 release | TBD | Human 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.
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.
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 re