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short-video-agent-kit

Agent-first short-form AI video generation CLI and MCP server for Sora, Veo, xAI and Seedance

Install / Use

claude mcp add davidmosiah -- npx -y github:davidmosiah/short-video-agent-kit

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

78/100

Category

Automation

Supported Platforms

Claude Code
Claude Desktop
Gemini CLI
OpenAI Codex

Tags

Our assessment of short-video-agent-kit

short-video-agent-kit scores 78/100 on our quality scale, 2566th of 2,870 Automation skills we index.

Its MCP Server is 8.4 KB long, well organised into 14 sections with 15 code examples: a thorough specification that gives an agent plenty to work with.

It has 3 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
29/30
Structure
20/20
Description
12/15
Adoption
3/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 8 days ago, so short-video-agent-kit is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 87/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

short-video-agent-kit compared with similar skills

All 4 of these similar skills score higher than short-video-agent-kit; compare them before choosing.

SkillScoreStarsUpdatedFormat
short-video-agent-kit (this skill)by davidmosiah7838d agoMCP Server
Agent-Reachby Panniantong100106.6k5d agoCLAUDE.md
headroomby headroomlabs-ai10078.3ktodayCLAUDE.md
CowAgentby zhayujie10047.7ktodayCLAUDE.md
Scraplingby D4Vinci10090.4k1d agoMCP Server

Frequently asked questions

How do I install short-video-agent-kit?
Run claude mcp add davidmosiah -- npx -y github:davidmosiah/short-video-agent-kit. The install tabs above show the steps for each supported agent.
Which AI agents does short-video-agent-kit work with?
It is written for Claude Code, Claude Desktop, Gemini CLI and OpenAI Codex, as a MCP Server file. Other agents that read the same format can often use it too.
Is short-video-agent-kit safe to use?
It is MIT-licensed and scores 87/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is short-video-agent-kit still maintained?
The repository was last updated 8 days ago, so short-video-agent-kit is actively maintained.
<!-- delx header v2 --> <h1 align="center">Short Video Agent Kit</h1> <div align="center"> <img src="assets/banner.png" alt="Short Video Agent Kit" width="85%" /> </div> <h3 align="center"> One agent-first CLI + MCP for short-form AI video.<br>Sora · Veo · xAI · Seedance &mdash; dry-run by default, paid generation when explicitly enabled. </h3> <p align="center"> <a href="https://www.npmjs.com/package/short-video-agent-kit"><img src="https://img.shields.io/npm/v/short-video-agent-kit?style=for-the-badge&labelColor=0F172A&color=10B981&logo=npm&logoColor=white" alt="npm version" /></a> <a href="https://www.npmjs.com/package/short-video-agent-kit"><img src="https://img.shields.io/npm/dm/short-video-agent-kit?style=for-the-badge&labelColor=0F172A&color=0EA5A3&logo=npm&logoColor=white" alt="npm downloads" /></a> <a href="LICENSE"><img src="https://img.shields.io/badge/LICENSE-MIT-22C55E?style=for-the-badge&labelColor=0F172A" alt="License MIT" /></a> <a href="https://modelcontextprotocol.io"><img src="https://img.shields.io/badge/BUILT_FOR-MCP-7C3AED?style=for-the-badge&labelColor=0F172A" alt="Built for MCP" /></a> </p> <p align="center"> <a href="https://github.com/davidmosiah/short-video-agent-kit/stargazers"><img src="https://img.shields.io/github/stars/davidmosiah/short-video-agent-kit?style=for-the-badge&labelColor=0F172A&color=FBBF24&logo=github" alt="GitHub stars" /></a> <a href="https://github.com/davidmosiah/short-video-agent-kit/actions/workflows/ci.yml"><img src="https://github.com/davidmosiah/short-video-agent-kit/actions/workflows/ci.yml/badge.svg" alt="CI status" /></a> <a href="https://github.com/davidmosiah"><img src="https://img.shields.io/badge/PART_OF-Delx_Agent_Stack-0EA5A3?style=for-the-badge&labelColor=0F172A" alt="Part of the Delx agent stack" /></a> <a href="https://github.com/davidmosiah/short-video-agent-kit"><img src="https://img.shields.io/badge/CATEGORY-Reach-7C3AED?style=for-the-badge&labelColor=0F172A" alt="Category" /></a> </p>

⭐ If this agent-first tool helps your workflow, please star the repo. Stars make this tooling easier for other builders to discover and help Delx keep shipping open infrastructure.<br> 🧱 Part of the Delx agent stack — 15 open-source MCP servers across body, reach and coordination.


HTTP (v2 stateless)

Default is stdio. Optional Streamable HTTP — no session id, JSON responses, loopback only:

npx -y -p short-video-agent-kit short-video-mcp --http
# GET  http://127.0.0.1:3033/health
# POST http://127.0.0.1:3033/mcp   (sessionless)

Env: SHORT_VIDEO_MCP_HOST, SHORT_VIDEO_MCP_PORT, SHORT_VIDEO_MCP_TRANSPORT=http.

<!-- /delx header v2 -->

Provider-neutral short-form AI video toolkit for agents. It gives Codex, Claude, Cursor, Hermes, OpenClaw and other MCP clients one interface for building dry-run payloads and, when explicitly enabled, generating vertical video through Sora/OpenAI, Gemini Veo, xAI/Grok and Seedance/PiAPI-style providers.

Use it when an agent needs one safe interface for prompt-to-video payload validation and optional paid generation across multiple providers.

Why It Is Agent-First

Video generation can be expensive and prompt-sensitive. This package makes agents start with safe steps:

  • inspect provider readiness
  • return privacy boundaries
  • build payloads without spending credits
  • require --live or SHORT_VIDEO_DRY_RUN=false before provider calls
  • keep prompts and outputs in local user-controlled paths

Install

npm install -g short-video-agent-kit

Or run directly:

npm exec --yes --package=short-video-agent-kit -- short-video-agent-kit doctor

Quickstart

No API key needed to try it — generation is dry-run by default, so the kit returns the exact provider-neutral plan it would send without spending a credit.

Build a Sora plan for an 8-second vertical teaser:

short-video-agent-kit generate \
  --provider openai_sora \
  --prompt "Vertical 8-second product teaser for a minimalist water bottle, soft studio light, slow dolly-in" \
  --output ./output/teaser.mp4

Real output (no provider call, no credits spent):

{
  "ok": true,
  "dry_run": true,
  "next_step": "Pass --live or set SHORT_VIDEO_DRY_RUN=false to call the provider API.",
  "provider": "openai_sora",
  "endpoint": "POST /v1/videos",
  "payload": {
    "model": "sora-2",
    "prompt": "Vertical 8-second product teaser for a minimalist water bottle, soft studio light, slow dolly-in",
    "seconds": "8",
    "size": "720x1280"
  }
}

Same prompt, different provider — the plan re-targets the endpoint and parameter shape for you. payload returns just the plan (no dry_run wrapper):

short-video-agent-kit payload --provider gemini_veo --prompt "Same teaser, 9:16, cinematic"
{
  "provider": "gemini_veo",
  "endpoint": "POST /models/{model}:predictLongRunning",
  "payload": {
    "instances": [
      {
        "prompt": "Same teaser, 9:16, cinematic"
      }
    ],
    "parameters": {
      "aspectRatio": "9:16",
      "durationSeconds": 8
    }
  }
}

Check which providers are wired up (keys are detected, never printed):

short-video-agent-kit doctor
{
  "ok": false,
  "dry_run": true,
  "providers": {
    "openai_sora": { "configured": false, "env_keys": ["OPENAI_API_KEY"], "models": ["sora-2"] },
    "gemini_veo": { "configured": false, "env_keys": ["GEMINI_API_KEY", "GOOGLE_API_KEY"], "models": ["veo-3.1-fast-generate-preview"] },
    "xai_grok": { "configured": false, "env_keys": ["XAI_API_KEY"], "models": ["grok-imagine-video", "grok-imagine-image"] },
    "seedance_piapi": { "configured": false, "env_keys": ["PIAPI_KEY", "SEEDANCE_API_KEY"], "models": ["seedance-2-fast-preview"] }
  },
  "output_dir": "./output",
  "next_steps": [
    "Set one provider key: OPENAI_API_KEY, GEMINI_API_KEY, XAI_API_KEY or PIAPI_KEY."
  ]
}

When you are ready to actually render, set a provider key and re-run generate with --live (or SHORT_VIDEO_DRY_RUN=false).

CLI

short-video-agent-kit manifest --client codex
short-video-agent-kit doctor
short-video-agent-kit privacy-audit
short-video-agent-kit payload --provider gemini_veo --prompt-file prompt.txt
short-video-agent-kit generate --provider openai_sora --prompt "Vertical product teaser" --output ./output/teaser.mp4
short-video-agent-kit generate --provider openai_sora --prompt-file prompt.txt --output ./output/teaser.mp4 --live

Supported providers:

  • openai_sora
  • gemini_veo
  • xai_grok
  • seedance_piapi

MCP

short-video-mcp

HTTP transport:

SHORT_VIDEO_MCP_TRANSPORT=http short-video-mcp

Hermes-style config:

mcp_servers:
  short_video:
    command: npx
    args: ["-y", "short-video-agent-kit"]
    sampling:
      enabled: false

Recommended first calls:

  1. short_video_connection_status
  2. short_video_privacy_audit
  3. short_video_build_payload
  4. short_video_generate

Agent Surfaces

| Tool | Purpose | |---|---| | short_video_agent_manifest | Install/runtime guidance for Codex, Claude, Cursor, Hermes and OpenClaw | | short_video_connection_status | Provider readiness without API keys | | short_video_privacy_audit | Prompt, output and reference-asset boundaries | | short_video_build_payload | Provider-specific payload without paid generation | | short_video_generate | Dry-run by default, live only when explicitly requested |

Copy-Paste Agent Prompt

Use short-video-agent-kit. First call short_video_connection_status and short_video_privacy_audit.
Build the payload before generation. Only set live=true if I explicitly confirm a paid provider call.

Configuration

Copy .env.example to .env and fill only the provider keys you plan to use. .env, output/ and .agent-data/ are ignored by Git.

Safety Model

  • Dry-run is the default.
  • API keys are never returned by tools.
  • Paid generation requires --live, MCP live=true, or SHORT_VIDEO_DRY_RUN=false.
  • Reference images must be user-owned or licensed.
  • Outputs are written to local paths controlled by the user.

Development

npm install
npm test
npm run check

📧 Contact & Support

  • 📨 support@delx.ai — general questions, integration help, partnerships
  • 🐛 Bug reports / feature requests — GitHub Issues
  • 🐦 Updates — @delx369 on X
  • 🌐 Site — wellness.delx.ai

Related Skills

View on GitHub
GitHub Stars3
CategoryAutomation
Updated8d ago
Forks1

Languages

JavaScript

Trust signals

87/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

2 low