mcp-video

<p align="center"> <a href="https://kyanitelabs.tech"> <img src="assets/kinocut-hero.webp" alt="Kinocut - guardrailed video editing for AI agents" width="100%"> </a> </p> <!-- mcp-name: io.github.KyaniteLabs/kinocut --> <h1 align="center">Kinocut</h1> <p align="center"> <strong>Guardrailed video editing MCP server for AI agents.</strong><br> 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. </p> <p align="center"> <a href="https://pypi.org/project/kinocut/"><img src="https://img.shields.io/pypi/v/kinocut.svg" alt="PyPI"></a> <a href="https://kinocut.dev/"><img src="https://img.shields.io/badge/site-kinocut.dev-0A0A0A" alt="kinocut.dev"></a> <a href="https://git.kyanitelabs.tech/KyaniteLabs/kinocut/actions"><img src="https://img.shields.io/badge/Forgejo%20CI-actions-blue" alt="CI"></a> <img src="https://img.shields.io/badge/MCP-196%20tools-orange.svg" alt="196 MCP tools on development tip"> <img src="https://img.shields.io/badge/CLI-167%20commands-orange.svg" alt="167 CLI commands on development tip"> <img src="https://img.shields.io/badge/python-3.11%2B-blue.svg" alt="Python 3.11+"> <img src="https://img.shields.io/badge/license-Apache%202.0-blue.svg" alt="Apache 2.0"> </p> <p align="center"> <a href="#see-it-work">Demo</a> &bull; <a href="#status-and-releases">Status</a> &bull; <a href="#whats-in-1133-latest-release">1.13.2</a> &bull; <a href="#changelog">Changelog</a> &bull; <a href="#beyond-1132-draft--gated">Beyond</a> &bull; <a href="#installation">Install</a> &bull; <a href="#quick-start">Quick Start</a> &bull; <a href="#mcp-tools">Tools</a> &bull; <a href="docs/TOOLS.md">Tool Reference</a> &bull; <a href="docs/RESCUE.md">Rescue</a> &bull; <a href="docs/AI_VIDEO_REVIEW_AND_SALVAGE.md">AI-video</a> &bull; <a href="#agent-skill">Agent Skill</a> &bull; <a href="https://kinocut.dev/">kinocut.dev</a> &bull; <a href="#what-is-kinocut">What is Kinocut?</a> &bull; <a href="#faq">FAQ</a> &bull; <a href="llms.txt">llms.txt</a> </p> > 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?](#what-is-kinocut) - [See It Work](#see-it-work) - [Installation](#installation) - [Quick Start](#quick-start) - [MCP Tools](#mcp-tools) - [Status and releases](#status-and-releases) - [Changelog](#changelog) - [FAQ](#faq) - [Agent Skill](#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 as** | `kino` (CLI); formerly **mcp-video** / `mcp_video` | | **Latest published release** | **[1.13.4](https://github.com/KyaniteLabs/kinocut/releases/tag/v1.13.4)** (2026-08-12) | | **Product site** | [kinocut.dev](https://kinocut.dev/) | | **PyPI** | [`kinocut`](https://pypi.org/project/kinocut/) | | **MCP Registry** | [`io.github.KyaniteLabs/kinocut`](https://registry.modelcontextprotocol.io/v0/servers/io.github.KyaniteLabs%2Fkinocut/versions/latest) | | **Source** | [GitHub](https://github.com/KyaniteLabs/kinocut) (public collab) · [Forgejo](https://git.kyanitelabs.tech/KyaniteLabs/kinocut) (**canonical source**) | | **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`](llms.txt) · site: [kinocut.dev/llms.txt](https://kinocut.dev/llms.txt). ## 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: ```python 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](docs/INSTALL.md) · [Golden path](docs/GOLDEN_PATH.md) · [Prompts](docs/PROMPTS.md) · [Tutorial](docs/TUTORIAL_PODCAST_TO_SHORTS.md) · [Compare](docs/COMPARE.md) · [When to recommend](docs/RECOMMEND.md) ## Status and releases | Surface | Version / tip | What it means | | --- | --- | --- | | **PyPI / npm / GitHub Release** | **[1.13.4](https://github.com/KyaniteLabs/kinocut/releases/tag/v1.13.4)** (2026-08-12) | Latest **published** Kinocut. Install with `pip install kinocut`. | | **This repository (`master`)** | **1.13.2** · **196 MCP tools / 167 CLI commands** | Intent/watching/TE + still/plate surface matches published package. | | **Next public release** | **TBD** | Post-release pillars and human programs remain gated; further bumps need a new go-ahead. | Install from PyPI when you want the stable package. Clone or install from `master` only when you intentionally need unreleased surfaces. ## What's in 1.13.2 (latest release) Kinocut **1.13.2** is what you get from `pip install kinocut` today. It is a patch release that adds **critical/high security hardening** plus **post-release correctness fixes** on top of the **1.13.1** feature baseline, which introduced the intent/watching/TE multiplier surface on top of still/plate (1.12) and the 1.11.x identity line: - **Intent-verb surface** — Semantic intent routing via `video_intent` / `intent` tools supporting ~10 verbs to dry-run plans without silent media mutations. - **Watching guardrail floor** — Validation and quality checkpoints (`video_review_run`, `video_review_decide`) performing metric QC (blackdetect/LUFS) and narrative first-15s inspection. - **B-roll proposals** — `video_propose_broll` / `propose-broll` for human-reviewable, non-silent B-roll insertion. - **Caption translation** — ES-first captions translation (`video_translate_captions`) and a language coverage honesty matrix. - **Trusted execution (TE) QoL & tooling** — QoL additions including `init`, `estimate`, `brand-kit`, `cutfile-validate`, `publish-validate`, hook-candidates, and plans for audiograms, punch-zoom, and seek-frame. - **Still/plate editor** — `still-match` / `still-grade` / `still-gate` / `image-edit` / `still-package` (MCP + CLI + Client), with receipts and fail-closed cohesion gate ([docs/STILL_PLATES.md](docs/STILL_PLATES.md)). - **Canonical counts** — Grow public surface to **196 MCP tools** and **167 CLI commands** (fully synchronized across standard, test, and client interfaces). - **Project, docs, package metadata, and discovery surfaces** pointed at **[kinocut.dev](https://kinocut.dev/)**. - **Compatibility window** — `mcp-video==1.6.8` installs `kinocut==1.13.4`; `mcp_video` imports, `MCP_VIDEO_*` env vars, `~/.mcp-video` data, `mcp-video://` resources, and legacy receipt keys remain supported **on the 1.13.x line**. Also already on the published line from earlier 1.x surfaces: - Agent **workflow engine** (`video_workflow_*` / `workflow-*`) with plan, render, resume, variants, and hashed receipts - Dedicated **video rescue** plan/render/inspect pipeline ([docs/RESCUE.md](docs/RESCUE.md)) - **Post-rescue planning** tools (semantic timelines, EDLs, transforms, restoration, composition, autopilot, egress contracts) - **Layered compositing** with full-canvas blend modes, rotation/pivot, and `layer_plan` v2 receipts - Expanded preflight guardrails for filters, merge, audio, overlay/chroma, text, and layout mismatches Full notes: [CHANGELOG.md](CHANGELOG.md) · [v1.13.2 release](https://github.com/KyaniteLabs/kinocut/releases/tag/v1.13.2) ## Beyond 1.13.2 (draft / gated) **1.13.2 is the latest published release.** Live directory submissions, launch posts, and first-10 real-user runs remain operator/human residual (`docs/HUMAN_GATES.md`) and are **not** claimed complete. ### Staged and Gated Surfaces While the core FFmpeg editing, workflow engine, still/plate editing, AI-video review/salvage, and sound capabilities are fully integrated and published in **1.13.2**, the following surfaces remain gated, partial, or unreleased: - **Desktop MCPB Packaging:** The staged desktop package (`mcpb/`) is a staged configuration and is **not** a published self-contained native runtime yet (pending FFmpeg provenance, licensing, and clean-machine gates). See [docs/MCPB.md](docs/MCPB.md). - **Sonic World Audio (`kinocut_sound`):** While the S1–S12 capabilities are integrated on the published line, the remaining slices are blocked or gated: - **S13 (Host Joins / bindings):** Blocked — external owner receipts incomplete. - **S14 (Dual-class Benchmark):** Partial — x86 available, Apple Silicon host unavailable. - **S15 (Adversarial Gate):** Gated under a release STOP — requires S13 receipts, dual-class benchmarks, and explicit human authorization. - **Trusted Execution Kernel:** The protected-timeline trusted execution kernel is post-program/gated and does not execute without the named upstream contract and human gating ([docs/plans/2026-07-09-kinocut-trusted-execution-layer.md](docs/plans/2026-07-09-kinocut-trusted-execution-layer.md)). - **Paid Generative / Dubbing Plans:** Generative spend-capped plans and TTS dubbing remain non-executable draft definitions until external backends and credentials are configured. Product checklist: [ROADMAP.md](ROADMAP.md). ## Agent Workflow Engine Agents can **plan, validate, render, recover, and prove** a multi-step local video job from a single JSON job-spec — through MCP (`video_workflow_*`), the CLI (`workflow-*`), or the Python client (`Client.workflow_*`) — with receipts strong enough for another agent or a human to trust before *and* after a render. Ops are a small allowlist (`probe | trim | resize | convert | merge | add_text | composite_layers`) mapped 1:1 to the same vetted engine functions the individual tools use; media references are symbolic and workspace-confined; everything fails closed. ```json { "schema_version": 1, "name": "captioned-vertical-short", "sources": { "hero": { "path": "input/hero.mp4" } }, "steps": [ { "id": "trim-hero", "op": "trim", "inputs": { "src": "@sources.hero" }, "params": { "start": 0, "duration": 6 }, "output": "@work/hero_trim.mp4" }, { "id": "vertical", "op": "resize", "inputs": { "src": "@work/hero_trim.mp4" }, "params": { "width": 1080, "height": 1920 }, "output": "@work/hero_vertical.mp4" }, { "id": "caption", "op": "add_text", "inputs": { "src": "@work/hero_vertical.mp4" }, "params": { "text": "Watch this", "position": "bottom-center" }, "output": "@outputs.master" } ], "outputs": { "master": { "path": "output/final.mp4" } } } ``` ```bash kino workflow-validate --spec job.json # cheap structural gate, no render kino workflow-plan --spec job.json --save-plan plan.json # dry-run op graph + hashes kino workflow-render --spec job.json --save-receipt receipt.json # execute + provenance receipt kino workflow-inspect --receipt receipt.json # read-only integrity re-check ``` The render receipt records per-step input/output hashes, a resume cursor, and a cleanup manifest, all with workspace-relative paths: ```json { "receipt_kind": "workflow", "versions": { "mcp_video": "1.13.2", "ffmpeg": "8.1" }, "spec_hash": "sha256:be2f3a9b...", "steps": [ { "id": "trim-hero", "op": "trim", "status": "completed", "input_hashes": { "src": "sha256:3b976d49..." }, "output": "work/be2f3a9b-2effedb3/mcp_video_hero_trim.mp4", "output_hash": "sha256:00727499..." }, { "id": "caption", "op": "add_text", "status": "completed", "output": "output/final.mp4", "output_hash": "sha256:8633ad2a..." } ], "cleanup_manifest": { "cleaned": true, "policy": "clean-on-success" }, "resume_cursor": { "last_completed_step": "caption", "next_step": null }, "status": "completed", "render_determinism_scope": "spec/input/output hashes are deterministic; rendered bytes may vary across FFmpeg builds" } ``` `--all-variants` emits N distinct outputs from one declaration, and `--resume` continues a job that failed with its intermediates kept (fail-closed on a changed spec). Full schema, `@ref` grammar, variants, resume, and cleanup are in [docs/WORKFLOWS.md](docs/WORKFLOWS.md); a runnable spec is in [examples/workflows/](examples/workflows/captioned-vertical-short/). ## Governed AI-video review In **Kinocut**, a contract-first path is provided for agent-edited media that must stay attributable and reviewable: 1. **Ingest** the source into a private content-addressed project (`video_ingest` / `video-ingest`) 2. **Preflight + temporal inspection** on the stored asset (`video_preflight`, `video_inspect_temporal`) 3. **Verdict + acceptance** with exact human evidence (`video_verdict`, `video_acceptance_eval`) 4. **Bounded derivatives only** — audio-preserving body swap or allowlisted salvage recipes (`video_body_swap`, `video_salvage`), each with lineage and a fresh non-approved review slot There is no force/bypass flag. Analyzer output alone cannot approve. Stale, aliased, or protected inputs fail closed. Operating guide: [docs/AI_VIDEO_REVIEW_AND_SALVAGE.md](docs/AI_VIDEO_REVIEW_AND_SALVAGE.md). These surfaces are fully integrated in the published 1.13.2 release — see [Status and releases](#status-and-releases). ## Dedicated Video Rescue For "fix this clip" requests where the story and timeline must remain unchanged, use the review-first rescue pipeline. Plan and inspect the diagnosis, approve only safe repair IDs, render, then inspect the verified package. The source stays immutable; master and universal sharing copy are always verified; optional captions remain sidecars. See [docs/RESCUE.md](docs/RESCUE.md) for CLI, MCP, Python, cancellation, resume, and stable errors. ## Layered Compositing `composite-layers` / `video_composite_layers` adds a spec-driven ordered layer stack for agents that need more than two-shot overlay primitives. It supports image, video, and solid layers; normal alpha compositing; per-layer opacity; x/y placement; transform sizing; timing windows; and mask/matte alpha sources — plus **full-canvas blend modes** (`multiply`, `screen`, `overlay`, `darken`, `lighten`) and **rotation** with a new `pivot` reference point. Dry-run plans and deterministic `layer_plan` v2 receipts capture source, filtergraph, and output hashes. ```bash kino composite-layers --spec layers.json --dry-run --save-layer-plan layer-plan.json kino composite-layers --spec layers.json -o out.mp4 --save-layer-plan layer-plan.json ``` Use `composite-layers` when an agent needs a planned stack of overlays, mattes, lower thirds, blurback plates, or platform variants that should be reviewed before rendering. A non-`normal` blend layer must be full-canvas (position `{0,0}`, full opacity, no scale/mask/timing) or it fails closed; output is video-only. Positioned/scaled/masked/timed blend, rotation + mask, and per-layer effect routing are tracked as later phases so this surface stays deterministic and preflightable. ## Still / Image Editing Kinocut treats multi-still packages as first-class media — plan → receipt → fail-closed gate, same safety posture as video rescue. Requires `pip install "kinocut[image]"`; run `kino doctor` to verify the image stack. **Workflow:** establish a hero plate → edit beats toward it → match shared WB/exposure → grade (optional signal LUT) → cohesion gate. ```bash # Image analysis: extract colors, generate palettes, analyze products kino image-extract-colors product.jpg -n 8 kino image-generate-palette scene.png --harmony triadic kino image-analyze-product listing.jpg --use-ai # Still/plate editing: match package to hero, grade, gate kino still-match --hero establish.png --inputs beat1.png beat2.png --output-dir out/matched kino still-grade --inputs out/matched/*.png --hero establish.png --output-dir out/graded kino still-gate --inputs out/graded/*.png --output-dir out/gate # Establish-locked edit with plan/receipt (dry-run first) kino image-edit --source beat.png --reference establish.png \ --intent "match establish world and light" --output-dir out/edit --dry-run # Or run the full pipeline in one shot kino still-package --establish establish.png --beats beat1.png beat2.png --output-dir out/pkg ``` ```python from kinocut import Client c = Client() c.still_match(hero="establish.png", inputs=["a.png", "b.png"], output_dir="out/m") c.still_gate(inputs=["out/m/a_matched.png", "out/m/b_matched.png"], output_dir="out/g") ``` `still-gate` fails closed on luma spread and shadow green/cyan metrics; every tool writes a JSON receipt with hashes and gains. Paid generative backends stay off by default (`prefer=edit`, `allow_paid_gen=false`). Full guide: [docs/STILL_PLATES.md](docs/STILL_PLATES.md). ## Public Discovery Kinocut is built to be **findable and citable** by both search engines and AI answer engines: - Canonical product URL: **https://kinocut.dev/** - GitHub README + [`llms.txt`](llms.txt) with entity facts, install commands, and safety rules - Official MCP Registry record under `io.github.KyaniteLabs/kinocut` - FAQ answers in this README and [docs/faq.md](docs/faq.md) (answer-first, versioned claims) ### Kinocut vs raw FFmpeg (and vs cloud editors) | | Kinocut | Raw FFmpeg in agent shell | Typical cloud editor API | | --- | --- | --- | --- | | Interface | Typed MCP / Python / CLI | Free-form flags | Hosted HTTP API | | Preflight | Guardrails before render | Agent invents flags | Vendor-specific | | Provenance | Video Receipts + hashes | Ad-hoc logs | Vendor dashboard | | Media location | Local-first | Local | Upload required | | Core cost | Free (Apache-2.0) | Free | Often metered | ## Why It Exists AI agents can write FFmpeg commands, but they should not have to guess flags, parse brittle stderr, or silently publish broken media. Kinocut gives agents typed operations, inspectable tool metadata, structured results, preflight guardrails, and quality checkpoints so a video workflow can be automated and reviewed without turning into shell-command roulette. Use it when you want an AI assistant to: - trim, merge, resize, crop, rotate, transcode, or export video; - add text, subtitles, watermarks, overlays, filters, fades, effects, and transitions; - extract audio, normalize audio, synthesize audio, add generated audio, or create waveforms; - detect scenes, make thumbnails, generate storyboards, compare quality, and create release checkpoints; - match, grade, and gate still packages with establish-locked color cohesion, or analyze product images for colors and palettes; - scaffold cinematic projects, read STYLE_/NEG_ blocks, parse storyboard tables, and expand shot prompts; - create new Hyperframes projects, inspect rendered layouts, capture websites, generate local speech, remove backgrounds, and post-process the result with FFmpeg tools; - repurpose one source video into vertical, horizontal, and square local delivery packages with manifests and review artifacts; - drive repeatable media workflows from Claude Code, Cursor, Codex-style clients, scripts, or CI. ## Installation Prerequisite: [FFmpeg](https://ffmpeg.org/) must be installed and available on `PATH`. ```bash # macOS brew install ffmpeg # Ubuntu/Debian sudo apt install ffmpeg ``` Run without a global install: ```bash uvx --from kinocut kino doctor ``` Or install with pip: ```bash pip install kinocut kino doctor ``` For Claude Desktop-style MCPB installs, Kinocut includes a staged local package at `mcpb/` and a local build script: ```bash python3 scripts/build-mcpb.py ``` This package is honest about its runtime: it launches an existing Python environment with Kinocut installed and still requires local FFmpeg. Native self-contained bundles remain blocked pending FFmpeg provenance, licensing, and clean-machine gates. See [docs/MCPB.md](docs/MCPB.md). Optional **C2PA** signing for final MP4 exports is available on the development tip when `c2patool` and a manifest/signer are configured. Signing is off by default and only reports `signed` after a verification read succeeds. See [docs/C2PA_PROVENANCE.md](docs/C2PA_PROVENANCE.md). Hyperframes tools additionally need Node.js 22+ and a resolvable Hyperframes CLI. Install/pin Hyperframes in the active Node package layout, add `hyperframes` to `PATH`, or set `MCP_VIDEO_HYPERFRAMES_COMMAND`. ### Which extra do I need? The core install covers all FFmpeg editing tools. Optional features ship as extras — install only what you use: | You want | Install | Approx. extra size | |---|---|---| | Speech-to-text subtitles (Whisper) | `pip install "kinocut[transcribe]"` | ~1 GB (torch) | | Image analysis (colors, layout, contrast) | `pip install "kinocut[image]"` | ~50 MB | | Vocal/instrument stem separation | `pip install "kinocut[stems]"` | ~2 GB (torch + demucs) | | AI upscaling | `pip install "kinocut[upscale]"` | ~2 GB (Python ≤3.12) | | Procedural audio/music tools | `pip install "kinocut[audio]"` | ~30 MB (numpy) | | Everything AI | `pip install "kinocut[ai]"` | several GB | Mix freely, e.g. `pip install "kinocut[transcribe,image]"`. Run `kino doctor` afterward — it reports exactly which features are available and what is missing. ### Upgrading from mcp-video Kinocut preserves the original surface during the rename window. Existing installs can upgrade without changing code: ```bash pip install --upgrade mcp-video mcp-video doctor ``` `mcp-video==1.6.8` is a metadata-only compatibility installer for `kinocut==1.13.4`. The `mcp_video` import, `mcp-video` command, `MCP_VIDEO_*` environment variables, `~/.mcp-video` data directory, `mcp-video://` resource URIs, and existing receipt keys remain supported on the 1.13.x line. New integrations should use `kinocut`, `from kinocut import Client`, and the `kino` command. ## En español Kinocut es un servidor MCP de edición de video para agentes de IA. La última versión publicada es **1.13.2** (`pip install kinocut`, **194 herramientas MCP / 167 CLI**). La punta de desarrollo (`master`) coincide con ese surface publicado: FFmpeg tipado para recortar, unir, subtitular, mezclar audio, efectos y reutilizar contenido (Shorts, Reels, TikTok), motor de flujos (`workflow`) con recibos verificables, rescate de video, revisión AI-video gobernada y barreras de seguridad antes de renderizar. Programas humanos residuales (directorios, lanzamiento, first-10) no se reclaman completos. Requisito: [FFmpeg](https://ffmpeg.org/) instalado y disponible en el `PATH`. ```bash # macOS brew install ffmpeg # Ubuntu/Debian sudo apt install ffmpeg # Instalación y diagnóstico pip install kinocut kino doctor ``` Para Claude Code: ```bash claude mcp add kinocut -- uvx --from kinocut kino ``` `kino doctor` informa qué funciones están disponibles y qué falta instalar. La documentación completa está en inglés; los mensajes de error principales son bilingües. ## Quick Start ### Golden path (60 seconds) Prove the install works before wiring an agent host: ```bash pip install -e . # or: pip install kinocut kino doctor # required checks must pass python scripts/golden_path.py ``` Success criteria and failure recovery: [`docs/GOLDEN_PATH.md`](docs/GOLDEN_PATH.md). Shareable pack (receipt + quality + media): `python scripts/generate_golden_pack.py` → [`demo/golden-pack/`](demo/golden-pack/). ### Try the receipt-backed proof first From a clone of this repo, run the smallest confidence workflow before wiring an agent host: ```bash uv run --no-project --with kinocut python workflows/05-confidence-baseline/workflow.py uv run --no-project --with kinocut python workflows/benchmarks/run_confidence_benchmark.py ``` The workflow generates a tiny source clip, creates a checked vertical video, runs quality/release checkpoint steps, and writes `workflows/05-confidence-baseline/output/video_receipt.json`. Proof notes live in [`docs/proofs/`](docs/proofs/). Public marketing claims (version, tool counts, URLs) live in [`docs/public_claims.json`](docs/public_claims.json) and are CI-guarded. ### Claude Code ```bash claude mcp add kinocut -- uvx --from kinocut kino ``` ### Claude Desktop ```json { "mcpServers": { "kinocut": { "command": "uvx", "args": ["--from", "kinocut", "kino"] } } } ``` ### Cursor ```json { "mcpServers": { "kinocut": { "command": "uvx", "args": ["--from", "kinocut", "kino"] } } } ``` Then ask your agent: > Trim this interview into a 45-second vertical clip, add burned captions, normalize the audio, make a thumbnail, and create a release checkpoint before export. ## Agent Skill Kinocut includes a public agent skill at [`skills/kinocut/SKILL.md`](skills/kinocut/SKILL.md). Use `$kinocut` in compatible agent hosts when you want the agent to choose between the MCP server, CLI, and Python client while preserving the inspect, edit, verify, and human-review workflow. For path-based short-form packages from **current tools only** (no invented commands, no external publish), see [`skills/kinocut-repurpose/SKILL.md`](skills/kinocut-repurpose/SKILL.md). That skill is an explicit marketing seed; the durable kernel-backed repurposing product is still on the trusted-execution roadmap. ## Python Client ```python from kinocut import Client editor = Client() clip = editor.trim("interview.mp4", start="00:02:15", duration="00:00:45") caption_file = "captions.srt" editor.ai_transcribe(clip.output_path, output_srt=caption_file) captioned = editor.subtitles(clip.output_path, subtitle_file=caption_file) vertical = editor.resize(captioned.output_path, aspect_ratio="9:16") checkpoint = editor.release_checkpoint(vertical.output_path) print(checkpoint["thumbnail"]) print(checkpoint["storyboard"]) ``` ## CLI ```bash kino info interview.mp4 kino trim interview.mp4 -s 00:02:15 -d 45 kino video-ai-transcribe clip.mp4 --output captions.srt kino subtitles clip.mp4 captions.srt kino resize clip.mp4 --aspect-ratio 9:16 kino video-quality-check clip.mp4 kino repurpose clip.mp4 --platforms youtube-shorts instagram-reel tiktok kino image-extract-colors product.jpg kino still-package --establish hero.png --beats shot1.png shot2.png --output-dir out/stills ``` ## What Agents Can Do | Workflow | Example prompt | | --- | --- | | Social clips | "Turn this landscape recording into a captioned TikTok and YouTube Short." | | Podcast production | "Find the strongest segment, trim it, normalize audio, add chapters, and export." | | Product demos | "Create a short launch video from screenshots, title cards, and voiceover." | | Cinematic planning | "Create a style pack and storyboard, then render shot prompts for generation." | | Quality review | "Compare these two exports, make thumbnails, and flag visual or audio problems." | | Batch automation | "Convert this folder of clips to web-ready MP4 with consistent loudness." | | Code-created video | "Scaffold a Hyperframes composition, inspect it, render it, then add subtitles and a watermark." | | Local repurposing | "Turn this master clip into Shorts, Reels, TikTok, and YouTube assets with thumbnails and a manifest." | | Video rescue | "Diagnose this damaged clip, propose only safe repairs, render an approved package, and verify the receipt." | | Governed review (dev tip) | "Ingest this export into a project, run preflight and temporal inspection, write a verdict, and salvage only the broken region." | ## MCP Tools On the **published 1.13.2** surface (and matching tip), kino registers **196 MCP tools** and **167 CLI commands**. The table summarizes core categories — `search_tools` discovers the exact operation without loading every description. | Category | Count | Highlights | | --- | ---: | --- | | Core video editing | 32 | trim, merge, resize, crop, rotate, convert, overlays, subtitles, export, cleanup, templates, merge-compatibility guardrails | | Project-backed inspection | 3 | content-addressed ingest, unified preflight, temporal evidence packages | | Governed AI-video | 4 | exact-asset verdicts, acceptance evaluation, audio-preserving body swaps, lineage-bound salvage | | Agent workflow engine | 4 | validate, plan, render, resume, inspect multi-step jobs with provenance receipts | | Dedicated rescue | 3 | diagnose, approve, render, verify, quarantine, and resume local content-preserving repairs | | Post-rescue planning | 8 | semantic timelines/query, EDLs, visual transforms, restoration, composition, autopilot, explicit egress | | Cinematic creation | 4 | project scaffold, style-pack parsing, storyboard parsing, shot prompt expansion | | AI-assisted media | 11 | transcription, scene detection, upscaling, stem separation, silence removal, color grading | | Hyperframes | 18 | init, preview, render, snapshots, inspect, catalog, website capture, local TTS, transcription, background removal, diagnostics, benchmark, post-process | | Repurposing | 2 | dry-run manifests, platform-ready variants, thumbnails, storyboards, release checkpoints | | Procedural audio | 7 | synthesize, compose, presets, effects, sequences, generated audio, spatial audio, mix-parameter guardrails | | Visual effects | 8 | vignette, glow, noise, scanlines, chromatic aberration, luma key, mask, shape mask, bounded filter parameters | | Transitions | 3 | glitch, morph, pixelate | | Layout and motion | 6 | grid, picture-in-picture, split-screen, animated text, counters, progress bars, auto-chapters, layout mismatch warnings | | Analysis | 8 | scene detection, thumbnail, preview, storyboard, quality compare, metadata, waveform, release checkpoint | | Image analysis | 3 | extract colors, generate palettes, analyze product images | | Still / plate editing | 5 | still-match, still-grade, still-gate, image-edit, still-package — establish-locked color match with cohesion gate | | Discovery | 1 | `search_tools` | ```python from kinocut import Client editor = Client() matches = editor.search_tools("subtitle") print(matches["tools"]) ``` Full reference: [docs/TOOLS.md](docs/TOOLS.md) ## Agent-Safe Workflow For autonomous agents, the intended path is inspect, edit, verify, then ask a human to review release artifacts: ```python from kinocut import Client client = Client() print(client.inspect("trim")) result = client.pipeline( [ {"op": "trim", "input": "source.mp4", "start": "00:01:00", "duration": "00:00:45"}, {"op": "add_text", "text": "Launch clip", "position": "top-center"}, {"op": "normalize_audio"}, {"op": "resize", "aspect_ratio": "9:16"}, {"op": "export", "quality": "high"}, {"op": "release_checkpoint"}, ], output_path="final-short.mp4", ) ``` Safety contract: - Media-producing calls return structured results with output paths. - High-risk edit paths now run preflight guardrails before FFmpeg execution: filter bounds, merge compatibility, audio mix volume/timing, overlay/watermark/chroma opacity and similarity, animated text timing/overflow, and grid/split-screen mismatch warnings. - Analysis and discovery calls return structured JSON reports. - Tool discovery is available through `search_tools()` and `Client.inspect()`. - Unexpected keyword errors are converted into actionable `MCPVideoError` guidance. - Do not publish agent-generated video without `video_quality_check`, `video_release_checkpoint`, and human visual/audio inspection. - For governed AI-video derivatives, require stored identities, active human decision evidence, and a fresh review slot after every salvage or body-swap — never raw FFmpeg workarounds labeled as governed. ## Changelog **1.13.0** (2026-08-07): - Added **Intent-verb surface** (`video_intent` / `intent`), **Watching guardrail floor** (`video_review_run` / `video_review_decide`), **B-roll proposals** (`video_propose_broll`), **Caption translation ES-first** (`video_translate_captions`), and **Trusted execution (TE)** quality-of-life additions. - Expanded published surface to **196 MCP tools** and **167 CLI commands** (fully synchronized across standard, test, and client interfaces). - Hardened path validation for caption translation, brand kit, and OTIO exports. **1.12.0** (2026-08-07): - Added **Still/plate editor surface** (`still-match`, `still-grade`, `still-gate`, `image-edit`, `still-package`) with fail-closed cohesion gating. **1.11.x** (2026-07-24): - Added thin **`kinocut_sound`** S12 public join adapters (`sound-capabilities`, `sound-plan-validate`, `sound-mix-render`, etc.). - Post-theme security hardening to prevent absolute host-path leaks and ensure all discovered operations have fail-closed invoke paths. See [CHANGELOG.md](CHANGELOG.md) for full historical release notes, or view the [GitHub Releases](https://github.com/KyaniteLabs/kinocut/releases) page. ## FAQ ### What is Kinocut? Kinocut is a free, open-source MCP server, Python library, and `kino` CLI for AI-agent video editing. It wraps FFmpeg (and optional Hyperframes/Whisper extras) with preflight guardrails, Video Receipts, and quality checkpoints. It was formerly named **mcp-video**. ### How do I install it? ```bash brew install ffmpeg # or apt install ffmpeg pip install kinocut kino doctor claude mcp add kinocut -- uvx --from kinocut kino ``` ### Is it free and local-first? Yes. Apache-2.0, runs on your machine, no Kinocut account or API key required for the core surface, and media is not uploaded to a Kinocut cloud. ### Which agents work with it? Any MCP-compatible client that can run a local stdio server (Claude Code, Cursor, Windsurf, Cline, and similar). You can also use the Python client or CLI without an agent. ### How many tools are there? Published **1.13.2** documents **196 MCP tools / 167 CLI commands**. The development tip matches the published surface. ### Was it called mcp-video? Yes. `mcp-video==1.6.8` installs `kinocut==1.13.4`. Compatibility imports, CLI name, env vars, data dir, resource URIs, and receipt keys remain supported on the 1.13.x line. More answers: [docs/faq.md](docs/faq.md) · on-site FAQ: [kinocut.dev/#faq](https://kinocut.dev/#faq) ## Documentation - [Documentation map](docs/README.md) - [Product site](https://kinocut.dev/) - [Tool reference](docs/TOOLS.md) - [Python client reference](docs/PYTHON_CLIENT.md) - [CLI reference](docs/CLI_REFERENCE.md) - [Agent workflow engine](docs/WORKFLOWS.md) - [Video receipts](docs/VIDEO_RECEIPT.md) - [Video rescue](docs/RESCUE.md) - [Post-rescue planning](docs/POST_RESCUE_FEATURES.md) - [AI-video review and salvage](docs/AI_VIDEO_REVIEW_AND_SALVAGE.md) - [AI-video contracts](docs/AI_VIDEO_CONTRACTS.md) - [AI-video inspection](docs/AI_VIDEO_INSPECTION.md) - [C2PA provenance](docs/C2PA_PROVENANCE.md) - [MCPB packaging](docs/MCPB.md) - [Product roadmap](ROADMAP.md) - [Trusted execution layer plan](docs/plans/2026-07-09-kinocut-trusted-execution-layer.md) - [Wishlist / 1.8 program parallel plan](docs/plans/2026-07-12-wishlist-parallel-execution.md) - [Sound program status](docs/status/2026-07-13-sound-program-strategic-handoff.md) - [AI agent discovery guide](docs/AI_AGENT_DISCOVERY.md) - [FAQ](docs/faq.md) - [Golden path (first-run proof)](docs/GOLDEN_PATH.md) - [Public claims (version / counts)](docs/public_claims.json) - [Golden demo pack](demo/golden-pack/README.md) - [Changelog](CHANGELOG.md) - [llms.txt](llms.txt) ## Testing Development verification lives in [docs/TESTING.md](docs/TESTING.md). Keep public-surface, media workflow, and security checks current when changing tool behavior. ## Development ```bash git clone https://git.kyanitelabs.tech/KyaniteLabs/kinocut.git cd kinocut python3 -m venv .venv source .venv/bin/activate pip install -e ".[dev]" pytest tests/ -v -m "not slow and not hyperframes" ``` ## Community - [Contributing](CONTRIBUTING.md) - [Code of Conduct](CODE_OF_CONDUCT.md) - [Governance](GOVERNANCE.md) - [Maintainers](MAINTAINERS.md) - [Security](SECURITY.md) - [Support](SUPPORT.md) - [Roadmap](ROADMAP.md) - [Changelog](CHANGELOG.md) - [GitHub issues](https://github.com/KyaniteLabs/kinocut/issues) ### Community deploys Operators who want a **public MCP URL** without opening home-router ports can study the community Apache-2.0 reference stack that puts Kinocut + Hyperframes behind Tailscale Funnel, Caddy, and Google OAuth (mcp-auth-proxy): [hyperframes-selfhost](https://github.com/ismailkattakath/hyperframes-selfhost) (not affiliated with KyaniteLabs; evaluate security for your threat model). ## License Apache 2.0. See [LICENSE](LICENSE). Built with [FFmpeg](https://ffmpeg.org/), [Hyperframes](https://hyperframes.io/), and the [Model Context Protocol](https://modelcontextprotocol.io/). --- ## Part of KyaniteLabs More from [KyaniteLabs](https://kyanitelabs.tech). Related projects: - **[Epoch](https://github.com/KyaniteLabs/Epoch)** — time-estimation MCP server (PERT) for AI agents - **[DialectOS](https://github.com/KyaniteLabs/DialectOS)** — Spanish dialect localization MCP server & CLI - **[checkyourself](https://github.com/KyaniteLabs/checkyourself)** — local-first production-readiness checks for AI-built code → More at **[kyanitelabs.tech](https://kyanitelabs.tech)** --- If Kinocut is useful to you, **[star or watch it](https://git.kyanitelabs.tech/KyaniteLabs/kinocut)** — it helps other agent builders find it. Built by **[Simon Gonzalez De Cruz](https://github.com/simongonzalezdc)** — available for Forward-Deployed / Applied-AI engineering and contract work via the public profile links above. <!-- s-plus-geo:start --> ## What is Kinocut? **Kinocut** is a **guardrailed video editing MCP server and CLI for AI agents** that helps **AI agent builders, Claude Code/Cursor users, and local media operators** **edit, caption, repurpose, and quality-gate video with typed FFmpeg tools**. | | | | --- | --- | | **Product** | Kinocut | | **Category** | guardrailed video editing MCP server and CLI for AI agents | | **Best for** | AI agent builders, Claude Code/Cursor users, and local media operators | | **Not** | a hosted cloud editor or untyped FFmpeg shell | | **Source** | [GitHub](https://github.com/KyaniteLabs/kinocut) · [Forgejo](https://git.kyanitelabs.tech/KyaniteLabs/kinocut) | | **Keywords** | video editing MCP, AI agent video, FFmpeg MCP, Shorts Reels | ## Who it's for - Primary: AI agent builders, Claude Code/Cursor users, and local media operators - Use when you need to edit, caption, repurpose, and quality-gate video with typed FFmpeg tools - Skip if you need a hosted cloud editor or untyped FFmpeg shell ## FAQ ### What is Kinocut? Kinocut is a guardrailed video editing MCP server and CLI for AI agents. It helps AI agent builders, Claude Code/Cursor users, and local media operators edit, caption, repurpose, and quality-gate video with typed FFmpeg tools. ### Who should use Kinocut? AI agent builders, Claude Code/Cursor users, and local media operators. ### How is Kinocut different? Unlike raw FFmpeg scripts or unguarded agent shells, Kinocut validates tools and emits receipts. ### Is Kinocut production software? Treat the README status and release tags as source of truth for maturity. Validate against your own requirements before production use. ## Status - Maintained as of 2026 on the default branch - Prefer release tags when pinning dependencies - Report issues on the canonical remote listed above ## Agent surface - Coding agents: read this README first, then repo docs/`AGENTS.md` if present - Prefer machine-readable briefs (`llms.txt`) when the repo ships one - MCP or skill entrypoints are documented in-repo when applicable ## Contributing Issues and PRs welcome on the canonical remote. Keep public docs free of secrets and machine-local paths. ## License See [LICENSE](LICENSE) in this repository (or package metadata if license is package-only). <!-- s-plus-geo:end -->