multimodal-reader-mcp
Analyzes local audio and video files using Google's Gemini AI models to extract summaries, timelines, transcripts, and observations.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@multimodal-reader-mcpanalyze /home/user/video.mp4 and summarize key moments"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
multimodal-reader-mcp
MCP server for reading local audio and video files with Google Gen AI and returning structured observations, timelines, and transcripts.
It analyzes a local media file and returns:
a short summary
a timeline of key moments
transcript snippets for spoken or visible text
key observations and notable signals
relevant clues tailored to the user's question
open questions plus a confidence level
Requirements
uvPython
3.14GOOGLE_API_KEY
Related MCP server: youtube-mcp
Model configuration
The default model is gemini-2.5-flash.
You can override the default model for all requests by setting:
MULTIMODAL_READER_MODEL
MCP client configuration
Example Cursor MCP config:
{
"mcpServers": {
"multimodal-reader": {
"command": "uvx",
"args": ["multimodal-reader-mcp"],
"env": {
"GOOGLE_API_KEY": "${env:GOOGLE_API_KEY}",
"MULTIMODAL_READER_MODEL": "gemini-2.5-flash"
}
}
}
}Tool
The package exposes one MCP tool:
read_media(file_path, question=None)
file_path must be an absolute path to a local media file.
This server cannot be installed
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