What does Videoindexer Mcp do?
It provides MCP tools to interact with Video Indexer APIs, specifically to generate and retrieve prompt content from video insights.
@benbakhar
Basic information
MCP server for using the Azure AI Video Indexer API
Add this server to your MCP-compatible client using the configuration below.
{
"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"
}
}
}Tool list not available yet
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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.
vi_prompt_content: Generate prompt content from video insightsvi_get_prompt_content: Retrieve generated prompt content for a videoIt provides MCP tools to interact with Video Indexer APIs, specifically to generate and retrieve prompt content from video insights.
Clone the repository, create a Python virtual environment, activate it, then run `pip install -r requirements.txt` followed by `pip install -e .`.
You must set the `VI_ACCOUNT_TOKEN` environment variable to your Video Indexer account token.
It uses `stdio` transport as shown in the example configuration.
Yes, the server is designed to feed LLMs with video insights via its `vi_prompt_content` and `vi_get_prompt_content` tools.
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