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cloudglue

Cloudglue MCP Server

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by cloudglue

search_video_summaries

Read-onlyIdempotent

Use natural language queries to semantically search video collections and find relevant videos based on content, summaries, and metadata. Returns results with relevance scores.

Instructions

AI-powered semantic search to find relevant videos within a collection. Uses Cloudglue's search API to locate videos based on their content, summaries, and metadata. Works with rich-transcripts and media-descriptions collections. Returns structured search results with video information and relevance scores. Perfect for discovering videos by topic, theme, or content similarity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_idYesCollection ID from list_collections without the 'cloudglue://collections/' prefix (e.g., use 'abc123' not 'cloudglue://collections/abc123'). Works with rich-transcripts and media-descriptions collections.
queryYesNatural language search query to find relevant videos. Examples: 'Find videos about pricing strategies', 'Show me customer complaint videos', 'Locate product demo videos', 'Find videos mentioning specific competitors'. Be specific about what you're looking for.
Behavior4/5

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

Annotations already declare readOnly, idempotent, and openWorld hints. The description adds context about the API used (Cloudglue's search API), valid collections, and return format (structured results with relevance scores), which enhances understanding beyond annotations.

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

Conciseness5/5

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

The description is five sentences, front-loaded with purpose, and each sentence adds value (purpose, API, collections, return type, use case). No redundancy or unnecessary information.

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?

The description covers purpose, collections, and return type, but lacks details on result fields (e.g., video IDs, scores) and pagination. Given no output schema, the agent has limited information to parse results.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds general context but does not provide new parameter-level details beyond the schema's explanations of collection_id prefix removal and query examples.

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

Purpose4/5

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

The description clearly states it performs semantic search to find relevant videos within a collection, specifying the verb ('search') and resource ('videos'). It differentiates from siblings like list_videos and retrieve_summaries, but does not explicitly contrast with search_video_moments, a similar sibling.

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

Usage Guidelines3/5

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

The description implies usage for discovering videos by topic, theme, or content similarity, but provides no explicit when-to-use or when-not-to-use guidance relative to sibling tools like search_video_moments.

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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