Skip to main content
Glama
Dmitriusan

mcp-youtube-intelligence

analyze_channel

Analyze a YouTube channel to extract channel details, video transcripts, and topic keywords. Accepts @handle, channel or /c/ URLs, and UCxxx IDs.

Instructions

Analyze a YouTube channel and return a JSON object with: channel_id, channel_title, channel_url, sample_video_ids[], videos_analyzed (count of videos fetched from playlist), transcripts_available (count with actual caption content), topics[] (top keyword frequencies across all transcripts), topics_structured[] (per-video semantic analysis — each entry has video_id/theme/entities[]/tags[]), note (which analysis mode ran), and optional output_path (local artifact path). Requires YOUTUBE_API_KEY and APIFY_TOKEN; set GEMINI_API_KEY for topics_structured semantic analysis (falls back to keyword-only when absent). Supported channel inputs: @handle (e.g. @fireship), youtube.com/@handle URL, /channel/UC... URL, bare 24-char UCxxxxxx ID, or legacy /c/ and /user/ URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_videosNoNumber of recent videos to analyze (default 5, max 50)
channel_urlYesYouTube channel URL or @handle (e.g. @fireship, https://www.youtube.com/@fireship, UCxxxxxxx)
Behavior4/5

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

With no annotations, the description carries full burden. It discloses output structure, dependencies, fallback mode, and input types. Missing details on rate limits or error handling, but still 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?

The description is verbose but every sentence adds useful information. It front-loads the output structure and maintains clarity. Could be slightly trimmed without losing value.

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

Completeness5/5

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

Given no output schema, the description fully explains the return object. Covers inputs, dependencies, and analysis modes, making it complete for a tool with two parameters.

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%, but description adds value by explaining accepted formats for channel_url and notes max_videos default/limit. Minor overlap with schema for max_videos.

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's purpose: analyze a YouTube channel and return a JSON object with specific fields. It distinguishes the resource and action without ambiguity.

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?

Provides clear context on when to use, including required API keys, fallback behavior, and supported input formats. However, it does not explicitly mention when not to use or alternatives, though no siblings exist.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Dmitriusan/mcp-youtube-intelligence'

If you have feedback or need assistance with the MCP directory API, please join our Discord server