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/kinocutLast scanned: 8/6/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-08-06T06:30:48.757Z",
"npmAuditRan": true,
"pipAuditRan": true,
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}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 158 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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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 | 1.15.1 (2026-08-31) |
| Product site | kinocut.dev |
| PyPI | kinocut |
| MCP Registry | io.github.KyaniteLabs/kinocut |
| Source | GitHub (canonical code, issues, PRs, CI, and releases) · Forgejo (downstream mirror; automated sync cutover pending verification) |
| 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 AI crawlers: llms.txt · site: kinocut.dev/llms.txt.
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 / GitHub Release | 1.15.1 (2026-08-31) | Latest published Kinocut. Install with pip install kinocut. |
This repository (master) |
Development tip · 201 MCP / 173 CLI | Adds four guarded local Revideo operations and verified sound mastering; not yet published. |
| 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 development-tip work such as the guarded Revideo operations; see docs/PRODUCT_MATTE.md for the published object-matte workflow.
Kinocut 1.15.1 is a maintenance release on top of 1.15.0: the mcp-video compatibility shim 1.6.12 carries the registry ownership marker, the legacy io.github.KyaniteLabs/mcp-video registry entry was republished so directory listings (Glama, PulseMCP) point at living metadata (#469), and the object-matte engine now streams decode with scratch-directory caps — bounded memory on large inputs (#414). Surface stays 196 MCP / 167 CLI — no new public tool name.
Kinocut 1.15.0 (2026-08-19) was the Windows/diagnostics release: first-class Windows support and honest diagnostics on top of 1.14.x (same 360 dual-cam assembly and performance surface), driven by a community bug report. Surface stays 196 MCP / 167 CLI — no new public tool name.
kino --mcp keeps the "requires the 'mcp' package" hint only when mcp is genuinely absent; every other server-tree import failure now prints its real cause (filesystem paths redacted, markup-safe) and exits non-zero. Reported in #445.mcp-server-import check imports the same server tree --mcp uses, so kino doctor can no longer report OK while MCP mode is broken.kino --mcp importable on Windows; lock errors follow a contention-only contract; kino --help no longer crashes on legacy cp1252 consoles; and a windows-latest CI smoke job (lint, import checks, kino doctor, public-surface tests) guards the platform on every change.360_assembly_plan (desk / table / front_back, split / switch / PiP / single) → approve → FFmpeg v360 render. MCP: video_intent goal= + video_review_decide. Python: Client.propose_360_assembly / decide_360_assembly / render_360_assembly. Raw .insv / .360 rejected. Director is a plug (local first; cloud opt-in). Not an optimized-AI claim. Guide: docs/360_ASSEMBLY.md.filter_complex (source audio kept); sampled quality-gate analyze window; SHA-256 path/mtime cache; merge can skip re-probe when infos= is supplied; batched 360 storyboard stills; lazy mcp_video / CLI / Client.search_tools; doctor skips npx --yes unless Hyperframes is already