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Video Understanding MCP Server

local only

Video Understanding MCP runs on your own machine — the client starts it, so there is no endpoint to ping. Last commit 9 Nov 2026.

Let AI agents watch videos and answer questions about them through any OpenAI-compatible endpoint.

—
Installs / week
npm · @granitebps/video-understanding-mcp
0
Stars
0 open issues
9 Nov 2026
Last commit
from GitHub
MIT
License
TypeScript

Nothing serious here today

Today is the operative word: we check Video Understanding MCP every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Three servers free · no card

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add video-understanding-mcp -e 'VIDEO_BASE_URL=<VIDEO_BASE_URL>' -e 'VIDEO_MODEL=<VIDEO_MODEL>' -- npx -y @granitebps/video-understanding-mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "video-understanding-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@granitebps/video-understanding-mcp"
      ],
      "env": {
        "VIDEO_BASE_URL": "<VIDEO_BASE_URL>",
        "VIDEO_MODEL": "<VIDEO_MODEL>"
      }
    }
  }
}
~/.codex/config.toml
[mcp_servers.video-understanding-mcp]
command = "npx"
args = ["-y", "@granitebps/video-understanding-mcp"]
env = { VIDEO_BASE_URL = "<VIDEO_BASE_URL>", VIDEO_MODEL = "<VIDEO_MODEL>" }
.cursor/mcp.json
{
  "mcpServers": {
    "video-understanding-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@granitebps/video-understanding-mcp"
      ],
      "env": {
        "VIDEO_BASE_URL": "<VIDEO_BASE_URL>",
        "VIDEO_MODEL": "<VIDEO_MODEL>"
      }
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "video-understanding-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@granitebps/video-understanding-mcp"
      ],
      "env": {
        "VIDEO_BASE_URL": "<VIDEO_BASE_URL>",
        "VIDEO_MODEL": "<VIDEO_MODEL>"
      }
    }
  }
}

Put your own values in place of <VIDEO_BASE_URL> (Base URL of an OpenAI-compatible chat completions endpoint whose model accepts video, e.g. https://host/v1), <VIDEO_MODEL> (Model (or router alias) to send videos to). The author’s registry entry marks them as required.

Optional settings from the registry entry, left out of the block above: VIDEO_API_KEY (Endpoint API key, sent as a bearer token), VIDEO_PART_FORMAT (How the video is attached: video_url, image_url, file, or input_file), VIDEO_MAX_DURATION_SECONDS (Longest analyzed range in seconds), VIDEO_MAX_UPLOAD_MB (Largest prepared video sent to the endpoint, in MB), VIDEO_ALLOWED_DIRS (Directories local files may be read from; local files are refused when unset), VIDEO_VERIFY_MEDIA (Fail calls when the endpoint evidently ignored the video).

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Video Understanding MCP — questions

Answers built from our own checks of this server.

Why is there no uptime for Video Understanding MCP?
Video Understanding MCP runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the npm package @granitebps/video-understanding-mcp.
How do I connect Video Understanding MCP?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It runs locally, so the command pulls @granitebps/video-understanding-mcp straight from npm; nothing to host, nothing to sign up for.
Is Video Understanding MCP open source?
Yes — it is published under the MIT licence, written in TypeScript and 0 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.