Video Still Capture MCP

A Model Context Protocol server for accessing and controlling webcams via OpenCV

Overview

Video Still Capture MCP is a Python implementation of the Model Context Protocol (MCP) that provides AI assistants with the ability to access and control webcams and video sources through OpenCV. This server exposes a set of tools that allow language models to capture images, manipulate camera settings, and manage video connections. There is no video capture.

Examples

Here are some examples of the Video Still Capture MCP server in action:

Orange Example

Left: Claude's view of the image	Right: Actual webcam capture

Magnet Example

Left: Claude's view of the image	Right: Actual webcam capture

Installation

Prerequisites

Python 3.10+
OpenCV (opencv-python)
MCP Python SDK
UV (optional)

Installation from source

git clone https://github.com/13rac1/videocapture-mcp.git
cd videocapture-mcp
pip install -e .

Run the MCP server:

mcp dev videocapture_mcp.py

Integrating with Claude for Desktop

macOS/Linux

Edit your Claude Desktop configuration:

# Mac
nano ~/Library/Application\ Support/Claude/claude_desktop_config.json
# Linux
nano ~/.config/Claude/claude_desktop_config.json

Add this MCP server configuration:

{
  "mcpServers": {
    "VideoCapture ": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "--with",
        "numpy",
        "--with",
        "opencv-python",
        "mcp",
        "run",
        "/ABSOLUTE_PATH/videocapture_mcp.py"
      ]
    }
  }
}

Ensure you replace /ABSOLUTE_PATH/videocapture-mcp with the project's absolute path.

Windows

Edit your Claude Desktop configuration:

nano $env:AppData\Claude\claude_desktop_config.json

Add this MCP server configuration:

{
  "mcpServers": {
    "VideoCapture": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "--with",
        "numpy",
        "--with",
        "opencv-python",
        "mcp",
        "run",
        "C:\ABSOLUTE_PATH\videocapture-mcp\videocapture_mcp.py"
      ]
    }
  }
}

Ensure you replace C:\ABSOLUTE_PATH\videocapture-mcp with the project's absolute path.

Using the Installation Command

Alternatively, you can use the mcp CLI to install the server:

mcp install videocapture_mcp.py

This will automatically configure Claude Desktop to use your videocapture MCP server.

Once integrated, Claude will be able to access your webcam or video source when requested. Simply ask Claude to take a photo or perform any webcam-related task.

Features

Quick Image Capture: Capture a single image from a webcam without managing connections
Connection Management: Open, manage, and close camera connections
Video Properties: Read and adjust camera settings like brightness, contrast, and resolution
Image Processing: Basic image transformations like horizontal flipping

Tools Reference

`quick_capture`

Quickly open a camera, capture a single frame, and close it.

quick_capture(device_index: int = 0, flip: bool = False) -> Image

device_index: Camera index (0 is usually the default webcam)
flip: Whether to horizontally flip the image
Returns: The captured frame as an Image object

`open_camera`

Open a connection to a camera device.

open_camera(device_index: int = 0, name: Optional[str] = None) -> str

device_index: Camera index (0 is usually the default webcam)
name: Optional name to identify this camera connection
Returns: Connection ID for the opened camera

`capture_frame`

Capture a single frame from the specified video source.

capture_frame(connection_id: str, flip: bool = False) -> Image

connection_id: ID of the previously opened video connection
flip: Whether to horizontally flip the image
Returns: The captured frame as an Image object

`get_video_properties`

Get properties of the video source.

get_video_properties(connection_id: str) -> dict

connection_id: ID of the previously opened video connection
Returns: Dictionary of video properties (width, height, fps, etc.)

`set_video_property`

Set a property of the video source.

set_video_property(connection_id: str, property_name: str, value: float) -> bool

connection_id: ID of the previously opened video connection
property_name: Name of the property to set (width, height, brightness, etc.)
value: Value to set
Returns: True if successful, False otherwise

`close_connection`

Close a video connection and release resources.

close_connection(connection_id: str) -> bool

connection_id: ID of the connection to close
Returns: True if successful

`list_active_connections`

List all active video connections.

list_active_connections() -> list

Returns: List of active connection IDs

Example Usage

Here's how an AI assistant might use the Webcam MCP server:

Take a quick photo:
```
I'll take a photo using your webcam.
```
(The AI would call quick_capture() behind the scenes)
Open a persistent connection:
```
I'll open a connection to your webcam so we can take multiple photos.
```
(The AI would call open_camera() and store the connection ID)
Adjust camera settings:
```
Let me increase the brightness of the webcam feed.
```
(The AI would call set_video_property() with the appropriate parameters)

Advanced Usage

Resource Management

The server automatically manages camera resources, ensuring all connections are properly released when the server shuts down. For long-running applications, it's good practice to explicitly close connections when they're no longer needed.

Multiple Cameras

If your system has multiple cameras, you can specify the device index when opening a connection:

# Open the second webcam (index 1)
connection_id = open_camera(device_index=1)

Troubleshooting

Camera Not Found: Ensure your webcam is properly connected and not in use by another application
Permission Issues: Some systems require explicit permission to access the camera
OpenCV Installation: If you encounter issues with OpenCV, refer to the official installation guide

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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