Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Description from the maker (original English)
Provider-neutral short-form AI video toolkit for agents: Sora, Gemini Veo, xAI/Grok, Seedance.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
SHORT_VIDEO_DRY_RUN, OPENAI_API_KEY, GEMINI_API_KEY, XAI_API_KEYValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"short-video-agent-kit": {
"command": "npx",
"args": [
"-y",
"short-video-agent-kit"
],
"env": {
"SHORT_VIDEO_DRY_RUN": "your-value",
"OPENAI_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"XAI_API_KEY": "your-value"
}
}
}
}Run this in your terminal
claude mcp add short-video-agent-kit --env SHORT_VIDEO_DRY_RUN=your-value --env OPENAI_API_KEY=your-value --env GEMINI_API_KEY=your-value --env XAI_API_KEY=your-value -- npx -y short-video-agent-kitFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"short-video-agent-kit": {
"command": "npx",
"args": [
"-y",
"short-video-agent-kit"
],
"env": {
"SHORT_VIDEO_DRY_RUN": "your-value",
"OPENAI_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"XAI_API_KEY": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"short-video-agent-kit": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"short-video-agent-kit"
],
"env": {
"SHORT_VIDEO_DRY_RUN": "your-value",
"OPENAI_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"XAI_API_KEY": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
SHORT_VIDEO_DRY_RUN envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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 9, 2026
The registry name was verified with the GitHub account davidmosiah, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 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.
You need to fill in: OPENAI_API_KEY, GEMINI_API_KEY, XAI_API_KEY
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).
The GitHub repo last changed –, and the latest version (0.1.7) reached the registry 5 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ 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.
Let any LLM watch a video locally — and search everything it has ever watched.
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.
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.
Short Video Agent Kit
One agent-first CLI + MCP for short-form AI video. Sora · Veo · xAI · Seedance — dry-run by default, paid generation when explicitly enabled.
⭐ 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.
🧱 Part of the Delx agent stack — 15 open-source MCP servers across body, reach and coordination.
Default is stdio. Optional Streamable HTTP — no session id, JSON responses, loopback only:
npx -y -p short-video-agent-kit short-video-mcp --http
Env: SHORT_VIDEO_MCP_HOST, SHORT_VIDEO_MCP_PORT, SHORT_VIDEO_MCP_TRANSPORT=http.
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.
Video generation can be expensive and prompt-sensitive. This package makes agents start with safe steps:
--live or SHORT_VIDEO_DRY_RUN=false before provider callsnpm install -g short-video-agent-kit
Or run directly:
npm exec --yes --package=short-video-agent-kit -- short-video-agent-kit doctor
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).
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_soragemini_veoxai_grokseedance_piapishort-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:
short_video_connection_statusshort_video_privacy_auditshort_video_build_payloadshort_video_generate| 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 |
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.
Copy .env.example to .env and fill only the provider keys you plan to use. .env, output/ and .agent-data/ are ignored by Git.
--live, MCP live=true, or SHORT_VIDEO_DRY_RUN=false.npm install
npm test npm run check