quick_captureLABSCO SUMMARY
Showing the capture next to the model's reading of it is the honest way to document a vision tool.
Most vision integrations demo the good case and let you discover the failure modes yourself. Putting the actual frame beside what the model said about it tells you what resolution and framing you will need to get a useful answer. The obvious caution is the obvious one: this connects a camera in your room to a model, so it belongs on a machine and in a moment where you have decided that is fine.
What it is
A small Python server that gives an assistant access to a connected camera through OpenCV, returning stills it can then examine.
What you get
Access to and control of a connected webcam, with captured stills handed back for the model to analyse. Their README shows the captures beside what the model made of them.
Requirements
Python 3.10+, OpenCV and the MCP Python SDK; uv optional. MIT licensed.
Setup effort
Build from source — clone the repository, then follow the project's own run instructions
USE CASES
01
Showing the model something physical
Point the camera, capture, ask.
02
Checking on a workspace
A still from a connected camera rather than a description.
7 tools
Listed in project docs. Your client may show a different list.
open_cameracapture_frameget_video_propertiesset_video_propertyclose_connectionlist_active_connectionsBEFORE YOU INSTALL
What to know first
Tools you get
7 tools named in the project's documentation.
Requires
- uv on PATH
- Python 3.10+
Where it runs
Both documented setups run the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
uv run --with mcp[cli] --with numpy --with opencv-python mcp run <YOUR_ABSOLUTE_PATH>/videocapture_mcp.pyMCP Clients
Claude Desktop — macOS / Linux
CLAUDE DESKTOP — MACOS / LINUX · JSON
{
"mcpServers": {
"VideoCapture ": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"--with",
"numpy",
"--with",
"opencv-python",
"mcp",
"run",
"<YOUR_ABSOLUTE_PATH>/videocapture_mcp.py"
]
}
}
}Claude Desktop — Windows
CLAUDE DESKTOP — WINDOWS · JSON
{
"mcpServers": {
"VideoCapture": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"--with",
"numpy",
"--with",
"opencv-python",
"mcp",
"run",
"C:\\ABSOLUTE_PATH\\videocapture-mcp\\videocapture_mcp.py"
]
}
}
}
