Skip to main content
Glama
Sign In
video-tools-mcp

video-tools-mcp

by video-context
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Detect shots

detect_shots
Read-only

Detect camera cuts in a video and return each shot with start and end times in seconds. Tune sensitivity and minimum shot length for scene-change analysis.

Instructions

Find the camera cuts in a video and return the shots between them, with start and end times in seconds.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "input": "<input>"
    },
    "name": "detect_shots"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputYesA local file path or an http(s) URL of a video.
min_shotNoIgnore cuts closer than this many seconds to the last cut. Default 0.5.
thresholdNoThe scene-change score that counts as a cut. Default 0.3. Lower finds more cuts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, so safety is already covered. The description adds useful output semantics beyond that: it returns the shots between cuts with start and end times in seconds. It doesn't discuss performance or edge cases, but it goes beyond what the annotations provide.

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?

A single efficient sentence that front-loads the action and result. Every clause earns its place with no redundancy.

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?

Given the simple read-only nature and full schema coverage, the description is adequate: purpose and return shape are clear. However, it lacks any guidance on when to choose this tool over its siblings, leaving a gap in a multi-tool video analysis context.

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 all three parameters are already documented with defaults and semantics. The description does not add any parameter-level detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb (find cuts / return shots) and resource (video), and clarifies the output form (shots with start/end times). It is distinguishable from siblings like extract_frames or check_keyframes, which serve different purposes.

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 on when to use this tool versus alternatives such as check_keyframes or video_context, nor any prerequisites or exclusions. The purpose is clear but the routing context is left entirely to inference.

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

Deploy Server

Other Tools