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Quick Start

The Cloudglue MCP server lets you connect AI assistants like Claude Desktop and Cursor to Cloudglue’s video understanding capabilities through the Model Context Protocol.

Using the Cloudglue MCP server, you can bring advanced video analysis, transcription, and extraction features directly into your favorite AI chat applications. This allows your AI assistants to understand, analyze, and extract insights from video content without leaving your workflow - whether you’re looking to transcribe meetings, extract structured data from video clips, or have conversations about video collections.

The video below walks through how to setup Cloudglue MCP server in a Claude Desktop client

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Setup

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1. Get API Key

Create a Cloudglue API key from cloudglue.dev. This key will authenticate the MCP server with your Cloudglue account.

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2. Configure MCP Client

Configure your MCP client (Claude Desktop or Cursor) to use the Cloudglue MCP server:

Claude Desktop uses a configuration file to manage MCP servers:

  1. Open the Claude menu on your computer and select “Settings…”
  2. Click on “Developer” in the left-hand bar of the Settings pane
  3. Click on “Edit Config”

This will open your claude_desktop_config.json file (located at ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows).

Add the following configuration to the file:

{
  "mcpServers": {
    "cloudglue": {
      "command": "npx",
      "args": [
        "-y",
        "@aviaryhq/cloudglue-mcp-server@latest"
      ],
      "env": {
        "CLOUDGLUE_API_KEY": "<YOUR-API-KEY>"
      }
    }
  }
}

Replace <YOUR-API-KEY> with your Cloudglue API key from step 1.

After updating the configuration, restart Claude Desktop completely.

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3. Verify Installation

Once configured:

  • In Claude Desktop: You should see a slider icon in the bottom left corner of the input box. Click it to see the available Cloudglue tools.
  • In Cursor: The Agent will automatically detect and use relevant Cloudglue tools when needed.

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Available Tools

Once configured, your AI assistant can access the following Cloudglue tools:

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Discovery & Navigation

  • list_collections: Discover available video collections and their basic metadata. Use this first to understand what video collections exist before using other collection-specific tools. Shows collection IDs needed for other tools, video counts, and collection types.

  • list_videos: Browse and search video metadata with powerful filtering options. Use this to explore available videos, find specific content by date, or see what’s in a collection. Returns essential video info like duration, filename, and IDs needed for other tools.

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Individual Video Analysis

  • get_video_description: Get comprehensive transcripts and descriptions from individual videos (YouTube or Cloudglue upload) with intelligent cost optimization. Automatically checks for existing transcripts before creating new ones. Supports customizable summarization.

  • get_video_entities: Extract structured data and entities from videos using custom prompts with intelligent cost optimization. Automatically checks for existing extractions before creating new ones. For individual videos - use retrieve_collection_entities for bulk collection analysis. The quality of results depends heavily on your prompt specificity.

  • get_video_metadata: Get comprehensive technical metadata about a Cloudglue video file including duration, resolution, file size, processing status, and computed statistics. Use this when you need video specifications, file details, or processing information rather than content analysis. Different from content-focused tools like get_video_description.

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Collection Analysis

  • retrieve_collection_transcripts: Bulk retrieve rich multimodal transcripts (text, audio, and visual) from a collection with advanced filtering. Use this for comprehensive analysis of multiple videos in a collection, when you need to compare transcripts, or analyze patterns across content. For single videos, use get_video_description instead. Use date filtering to focus on specific time periods.

  • retrieve_collection_entities: Batch retrieve structured entity data from multiple videos in a collection. Entities can be user-defined based on what’s important for your collection (people, objects, concepts, custom categories). Perfect for data mining, building datasets, or analyzing previously extracted entities at scale. Supports pagination and date-based filtering to manage large result sets. For individual video entities, use get_video_entities instead.

  • find_video_collection_moments: AI-powered semantic search to find specific moments, topics, or content within a video collection. Returns relevant segments with context, timestamps, and citations. Perfect for finding needle-in-haystack content, specific discussions, or thematic analysis across multiple videos. Much more targeted than bulk retrieval tools.

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When to Use Which Tool

  • Start with list_collections and list_videos to explore available content
  • For single videos: Use get_video_description or get_video_entities
  • For collections: Use retrieve_collection_* for bulk analysis or find_video_collection_moments for targeted searches
  • For technical specs: Use get_video_metadata

All tools include intelligent features like cost optimization, automatic fallbacks, and comprehensive error handling.

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Troubleshooting

If the MCP server isn’t working:

  1. Ensure you have Node.js installed (node --version in terminal)
  2. Verify your API key is correct
  3. Restart the client application completely
  4. Check logs for any error messages

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Resources