Skip to main content
Glama

Analyze Video

analyze_video

Extract information from videos by providing a prompt and a video source (URL or local file) for AI vision analysis.

Instructions

Analyze a video using AI vision models. Supports URLs and local file paths.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe prompt describing what you want to know about the video.
optionsNo
videoSourceYesVideo source - can be a URL or local file path
Behavior2/5

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

With no annotations, the description must disclose all behavioral traits. It only mentions source support and that it uses AI vision models, but omits details like processing time, file size limits, supported formats, or that it is a read operation.

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 two sentences, front-loading the purpose and source types. No redundant or extraneous words.

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

Completeness2/5

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

Given the complexity of video analysis (long processing, nested options, no output schema), the description is too sparse. It does not mention return format, prompt tips, or that processing may be slow.

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

Parameters2/5

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

The description adds little beyond the schema; it restates that video source can be a URL or path, which is already in the schema. With 67% schema coverage, the description should compensate for less documented options but fails to do so.

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 analyzes a video using AI vision models, and lists supported source types (URLs and local file paths). This verb+resource specification distinguishes it from sibling image-analysis tools.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like image analysis tools. The absence of any when-to-use or when-not-to-use information makes it difficult for an agent to choose correctly.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tan-yong-sheng/ai-vision-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server