Videoindexer Mcp
About
MCP server for using the Azure AI Video Indexer API
Details
- Author
- benbakhar
- GitHub stars
- 4
- Downloads
- 161
- Categories
- Other
Jump to
- vi_prompt_content: Generate prompt content from video insights
- vi_get_prompt_content: Retrieve generated prompt content for a video
- Feed LLMs with video insights
- Automated API interactions via MCP tools
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Videoindexer McpCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Clone the repository, create and activate a Python virtual environment, install dependencies with pip install -r requirements.txt, and install the package with pip install -e .. Configure the server with your Video Indexer account token in the VI_ACCOUNT_TOKEN environment variable and run via stdio transport. Invoke the provided tools vi_prompt_content and vi_get_prompt_content through your MCP client.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"videoindexer mcp": {
"videoindexer-mcp": {
"command": "/path/to/videoindexer-mcp/bin/python",
"args": [
"/path/to/your/videoindexer-mcp/src/main.py"
],
"env": {
"VI_ACCOUNT_TOKEN": "<your_video_indexer_account_token>"
},
"transportType": "stdio"
}
}
}
}McpServers
{
"videoindexer-mcp": {
"command": "/path/to/videoindexer-mcp/bin/python",
"args": [
"/path/to/your/videoindexer-mcp/src/main.py"
],
"env": {
"VI_ACCOUNT_TOKEN": "<your_video_indexer_account_token>"
},
"transportType": "stdio"
}
}Video Indexer MCP Server
A Model Context Protocol (MCP) server that provides tools and resources for interacting with Video Indexer APIs.Features
- vi_prompt_content: Generate prompt content from video insights
- vi_get_prompt_content: Get the generated prompt content for a video
Use Cases
- feed LLMs with video insights
- Automated API interactions
example config
{
"mcpServers": {
"videoindexer-mcp": {
"command": "/path/to/videoindexer-mcp/bin/python",
"args": [
"/path/to/your/videoindexer-mcp/src/main.py",
],
"env": {
"VI_ACCOUNT_TOKEN": "<your_video_indexer_account_token>",
},
"transportType": "stdio"
}
}
}
Replace /path/to/videoindexer-mcp with the actual path to your videoindexer-mcp directory.
Installation
1. Clone the repository
2. Create and activate a Python virtual environment:
# Create virtual environment
python -m venv mcp-env
Activate virtual environment
On Windows:
mcp-env\Scripts\activate
On Unix or MacOS:
source mcp-env/bin/activate
3. Install dependencies:
pip install -r requirements.txt
4. Install the package:
pip install -e .
5. To deactivate the virtual environment when you're done:
deactivate
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