Vlexor MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Vlexor MCP Serveredit my video to remove all silences"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@velxor/mcp
An MCP (Model Context Protocol) server that lets Claude Code, Cursor, and other MCP-capable agents drive all three Vlexor pillars — AI video editing, game-asset generation, and motion-graphics production — directly from a coding session.
Video editing runs on your own footage: your raw video never leaves your machine — only the text of your instructions (and an optional transcript) is sent to Vlexor to generate the edit plan, which is compiled to a real FFmpeg command and rendered entirely locally. Asset generation and motion graphics render server-side (there's no local footage to protect) and return a signed download URL — optionally saved straight to a local path.
Setup
Generate a personal API key at Vlexor → Settings → MCP & API.
Install FFmpeg if you don't already have it (
brew install ffmpegon macOS, or pointVLEXOR_FFMPEG_DIRat a folder that hasffmpeg/ffprobe).Add this to your MCP client's config:
{
"mcpServers": {
"vlexor": {
"command": "npx",
"args": ["-y", "@velxor/mcp"],
"env": { "VLEXOR_API_KEY": "vlx_…" }
}
}
}Related MCP server: Cognitive Core
Tools
Pillar 1 — video editing (renders locally; footage never uploaded):
probe_media— read a local video's duration, resolution, fps, codec.generate_edit_plan— natural-language instruction → structured edit plan (calls the real Vlexor Command Engine; counts against your plan's usage).compile_edit_plan— edit plan → a real FFmpeg command, computed entirely locally.render— run the compiled command locally to produce the final video.
A typical agent flow: probe_media → generate_edit_plan → (review the
steps) → compile_edit_plan → (review the FFmpeg command) → render.
Pillar 2 — asset generation (renders server-side):
generate_game_asset— prompt → a texture, 2D character, sprite sheet, 3D model (.glb), sound effect, music track, parallax background, or character turnaround. Returns a signed download URL; passsavePathto also write the file locally.
Pillar 3 — motion graphics (renders server-side):
generate_motion_graphic— a short creative brief → a rendered kinetic-title.mp4(announcement/promo card). Returns a signed download URL; passsavePathto also write the file locally.
Environment variables
Variable | Required | Default | Purpose |
| yes | — | Personal API key from Settings → MCP & API |
| no |
| Override for self-hosted/dev instances |
| no | (system | Folder containing |
About this repository
This package is the thin integration layer that connects an MCP client to
Vlexor's real, hosted API — every tool call here is a plain, inspectable
HTTP request (you can read exactly what leaves your machine in
src/api-client.ts). It's open so agent developers
piping their API key through it can verify that for themselves.
The Vlexor platform itself — the editing engine, the AI prompt design, the
asset/motion-graphics generation pipelines — is closed-source. A couple of
this package's imports (@velxor/engine's FFmpeg-plan compiler,
@velxor/shared's type definitions) come from that private codebase and
aren't published separately, so this repo won't pnpm install/build
standalone — it's meant to be read, and run via the pre-built npm package
(npx -y @velxor/mcp), not compiled from this checkout.
Issues and PRs on the MCP integration layer itself (tool schemas, error handling, the local FFmpeg orchestration) are welcome.
License
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