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Cloudglue MCP Server

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by cloudglue

extract_video_entities

Idempotent

Extract structured data and entities from videos using prompts or fetch pre-existing extractions from collections. Supports YouTube, Cloudglue, and direct video URLs with pagination.

Instructions

Extract structured data and entities from videos with intelligent cost optimization and pagination support. Two modes: (1) Fetch existing entities from an entities collection by providing collection_id (prompt not required) - retrieves previously extracted entities stored in that collection for the given Cloudglue file, returns error if not found, (2) Extract new entities by providing prompt (collection_id optional) - automatically checks for existing extractions before creating new ones. Supports YouTube URLs, Cloudglue URLs, and direct HTTP video URLs. The quality of results depends heavily on your prompt specificity. Pagination is supported - use the 'page' parameter to retrieve specific pages of segment-level entities. Use this for individual video analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesVideo URL to extract entities from. Supports multiple formats: • **Cloudglue platform (default)**: `cloudglue://files/file-id` - Use file ID from list_videos • **YouTube URLs**: `https://www.youtube.com/watch?v=...` or `https://youtu.be/...` • **Public HTTP video URLs**: Direct links to MP4 files (e.g., `https://example.com/video.mp4`) • **Data connector URLs** (requires setup in Cloudglue account): - **Dropbox**: Shareable links (`https://www.dropbox.com/scl/fo/...`) or `dropbox://<path>/<to>/<file>` - **Google Drive**: `gdrive://file/<file_id>` - **Zoom**: Meeting UUID (`zoom://uuid/QFwZYEreTl2e6MBFSslXjQ%3D%3D`) or Meeting ID (`zoom://id/81586198865`) See https://docs.cloudglue.dev/data-connectors/overview for data connector setup.
promptNoDetailed extraction prompt that guides what entities to find. Examples: 'Extract speaker names, key topics, and action items', 'Find product names, prices, and features mentioned', 'Identify companies, people, and technologies discussed'. Be specific about the data structure you want. Required when collection_id is not provided.
collection_idNoOptional collection ID to fetch previously extracted entities from an entities collection (saves time and cost). Use collection ID from list_collections. When provided with a Cloudglue URL, this tool retrieves existing entity extractions that were previously extracted and stored in the specified collection. Only works with Cloudglue URLs. When provided, prompt is not required and entities are fetched from the collection.
pageNoPage number for paginated segment-level entities. Each page contains 25 segment entities. Defaults to 0 (first page). Use this to retrieve segment entities for specific pages of longer videos.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide idempotentHint=true, and the description reinforces this by stating the tool automatically checks for existing extractions. It also discloses error behavior (returns error if not found) and mentions cost optimization. However, it does not describe output structure or comprehensive error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is clear and front-loaded but somewhat verbose, with redundancy on pagination (schema already covers it). The 'intelligent cost optimization' phrase is vague and adds little value. About 150 words, could be trimmed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers the two modes and pagination well, but lacks any description of the output format or structure. Since no output schema exists, the description should at least hint at what the agent will receive, e.g., entity types or JSON structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All four parameters have schema descriptions (100% coverage), and the description adds meaningful context: URL examples and reference, prompt examples, collection_id mode explanation, and page segment details. This goes beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool extracts structured data and entities from videos, with two distinct modes (fetch existing vs extract new) and supported URL types. It explicitly says 'Use this for individual video analysis,' distinguishing it from sibling tools like describe_video or search_video_moments.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use each mode based on whether collection_id or prompt is provided, and mentions pagination. However, it lacks explicit guidance on when not to use this tool or comparison with sibling tools beyond a brief final sentence.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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