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video-tools-mcp

video-tools-mcp

by video-context
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TypeScript
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Video context

video_context
Read-only

Extract media facts, shots, and keyframes from a local or remote video, building one JSON document in the Video Context schema for indexing and playback.

Instructions

Build one JSON document for a video in the open Video Context schema (https://github.com/video-context/video-schema): media facts, shots, and keyframes. For semantic search, transcripts, on-screen text, and objects across many videos, see Video Context: https://videocontextapi.com

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": "video_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputYesA local file path or an http(s) URL of a video.
thresholdNoThe scene-change score for shot detection. Default 0.3.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds that it produces a single JSON document and cites the output schema, useful structural context, but says nothing about cost, processing time, or error behavior for a video-analysis operation.

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

Conciseness4/5

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

Two sentences, front-loaded with what the tool produces, followed by the disambiguation clause. The external URL marketing line is slightly promotional but does carry the routing distinction, so little is wasted.

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?

With no output schema, the description should at least sketch the JSON shape it says it builds; instead it defers to an external GitHub link. For a tool whose whole purpose is assembling a structured document, this is a meaningful gap, though annotations and the cited schema cover part of the burden.

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 both parameters (input path/URL, threshold with default 0.3) are fully documented in the schema. The description adds nothing about them; baseline 3 applies.

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?

States a concrete verb (Build) and artifact (one JSON document for a video) and names the schema it conforms to, with a link. It also distinguishes itself from a differently-scoped external service for semantic search/transcripts, though that reference points outside the sibling set rather than to its actual siblings.

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 contrasts itself with a semantic-search API, implying 'use this for deterministic per-video media facts/shots/keyframes', but it never references the actual sibling tools (detect_shots, extract_frames, check_keyframes, video_metadata), which is where routing guidance matters most. Usage is implied rather than stated.

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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