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fetch_media

Fetches audio from any media URL to a local file for downstream analysis, returning the file path, title, and duration. Requires no API key.

Instructions

Download the best audio from a video/audio URL to a local file using yt-dlp. Returns the local path plus title and duration. No API key required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe media URL to download (any site yt-dlp supports).
formatNoOutput audio format (default: wav, which whisper.cpp prefers).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It reveals key traits: it uses yt-dlp, requires no API key, writes to a local file, and returns the local path plus title and duration. It does not warn about potentially long download times, network failures, or unsupported URLs, but the core side effects and return contract are disclosed.

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 with no filler. The primary action is front-loaded, followed by the return payload and a practical prerequisite (no API key), which are both useful and directly relevant to tool invocation.

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

Completeness4/5

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

The description covers the tool's purpose, return values, and a key prerequisite, and the schema handles parameters well. It is complete enough for typical use, but due to the absence of an output schema and annotations, additional context about failure modes, long-running operations, or unsupported URL categories would make it more robust.

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 schema already documents both parameters fully, including the format enum and the default of wav. The description adds little parameter-specific detail beyond mentioning 'best audio,' which is adequate given the high schema coverage.

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 uses a specific verb ('Download'), names the resource ('best audio from a video/audio URL'), and specifies the delivery mechanism ('to a local file using yt-dlp'). It is clearly distinguishable from sibling tools like transcribe_media and analyze_transcript, whose purposes center on transcription and analysis rather than fetching media.

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 makes the intended context clear: use this tool when you need to download audio from a media URL for local use, and the sibling names imply downstream transcription/analysis. However, it does not explicitly state when not to use it or name an alternative tool directly.

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