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neuron_grab_media

Extract and download video or audio from any page by capturing CDN streams from network traffic. Works on social media and embedded video sites, returning direct download URLs and status.

Instructions

Extract and download video/audio from any page. Navigates to the URL, plays the media to trigger network requests, searches captured traffic for video/audio streams (mp4, m3u8, webm, mp3, blob), extracts the CDN URLs, and initiates a browser download. Works on Instagram reels, TikTok videos, X/Twitter videos, Facebook videos, LinkedIn videos, YouTube, and most sites with embedded video. Returns the download URLs found and download status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPage URL containing the video (e.g. an Instagram reel URL, TikTok video URL)
tabIdNoUse an existing tab (optional)
filenameNoFilename to save as (optional — auto-generates from URL)
waitSecondsNoHow long to wait for video to start loading (default: 5)
preferQualityNoPreferred quality: 'highest', 'lowest', 'auto' (default: highest)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.4.1

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description takes on the transparency burden and succeeds: it discloses the multi-step side-effecting workflow (navigating, playing media, capturing network traffic, initiating a browser download). It also states the return information. It stops short of warning about DRM/auth/blocked sites, but the core behavior is transparent.

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?

All sentences contribute: purpose, method, supported scope, and return value. The platform/format list is long but functional, and the main purpose is front-loaded.

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?

For a no-output-schema tool with a multi-step workflow, the description explains enough to invoke it: what happens, how it finds media, and what is returned. It is slightly vague about the shape and meaning of 'download status' and silent on failure cases, but no critical selection or invocation detail is missing.

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 coverage is 100%, so the schema already documents all five parameters, including defaults and optionality. The description adds no parameter-specific detail beyond the schema, so baseline 3 is appropriate.

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?

The description uses an action verb ('Extract and download') and a concrete resource ('video/audio from any page'), then lists target platforms and media formats. It is easily distinguished from the surrounding navigation/inspection tools, though it never explicitly differentiates itself from neuron_grab_media_batch.

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?

It implies use on pages containing embedded video and enumerates supported platforms, which gives the agent a strong context signal. It does not state when to prefer an alternative (notably neuron_grab_media_batch for multiple URLs) or call out exclusions and limitations.

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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