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OpenRouter MCP Multimodal Server

OpenRouter MCP Multimodal Server

by stabgan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

analyze_video

Read-only

Transcribe or analyze video files by providing a local path, URL, or base64 data URL. Ask questions or get descriptions using a multimodal model.

Instructions

Analyze or transcribe a video file using a multimodal model. Accepts mp4, mpeg, mov, or webm from a local file path, HTTP(S) URL, or base64 data URL. Default model: google/gemini-2.5-flash.

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": {
      "video_path": "<video_path>"
    },
    "name": "analyze_video"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNoOverride the model ID.
questionNoQuestion or instruction about the video (default: describe).
video_pathYesFile path, HTTP(S) URL, or base64 data URL. Supported formats: mp4, mpeg, mov, webm.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.8.3

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds format details and default model but does not disclose behavioral traits like output format or side effects. Description is consistent with annotations but adds limited value beyond them.

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?

The description is concise with two sentences: first stating purpose, second covering formats and default model. No unnecessary information, though the structure could be slightly improved by front-loading the most critical info.

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 clarify what the tool returns (e.g., transcription or analysis text). It lacks this, and omits guidance on the 'question' parameter's behavior versus the default. Overall, it covers input basics but is incomplete regarding expected output.

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?

Schema coverage is 100% with detailed descriptions for all three parameters. The description adds the default model ('google/gemini-2.5-flash'), which is not in the schema, providing useful context. The rest of the parameter info is already covered by 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 analyzes or transcribes a video file using a multimodal model, specifies supported formats (mp4, mpeg, mov, webm), and mentions a default model. This distinguishes it from sibling tools like analyze_audio and analyze_image, which target other modalities.

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 implies usage for video content via the resource name and accepted formats, but does not explicitly state when to use this tool over alternatives or provide exclusions. The context is clear, but guidance is implicit.

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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