Videoindexer Mcp
About
Videoindexer Mcp is a Model Context Protocol (MCP) server that provides tools and resources for interacting with Video Indexer APIs. It enables developers to feed LLMs with video insights and automate API interactions.
Explore
- vi_prompt_content: Generate prompt content from video insights
- vi_get_prompt_content: Get the generated prompt content for a video
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
1. Clone the repository
2. Create and activate a Python virtual environment:
{
"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.
python -m venv mcp-env
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"
}
}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
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.
