Get details for a YouTube video: title, full description, channel name and ID, publish date, duration in seconds, view count, category, keywords, and thumbnail. Works for regular videos, Shorts, and live streams.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | YouTube video URL (watch?v=, youtu.be/, /shorts/, /embed/ or /live/ forms) or 11-character video ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly implies a read operation ('Get details') and discloses the return field set and supported video formats. It does not mention error behavior, authentication, or rate limits, but those are less critical for a read-only details tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the verb and resource, followed by a compact list of returned fields and supported video types. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read-only tool with no output schema, the description lists the key return fields and explicitly notes compatibility with regular videos, Shorts, and live streams. It is sufficient for an agent to select and invoke correctly, though it omits edge-case failure details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% parameter description coverage for the single 'url' parameter, listing all accepted URL forms and video ID format. The description adds no additional parameter semantics, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' with the resource 'details for a YouTube video' and enumerates the exact fields returned (title, description, channel, views, etc.). It also explicitly states coverage of regular videos, Shorts, and live streams, distinguishing it from channel or comment tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving metadata for a specific YouTube video but does not explicitly contrast with sibling tools like search_youtube, youtube_channel_details, or get_youtube_comments. No when-not guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly scoped by platform and resource (e.g. search_twitter vs twitter_user_tweets vs twitter_tweet_details). A few pairs like twitter_tweet_comments vs twitter_user_replies or facebook_page_posts vs search_facebook_posts could cause minor confusion, but descriptions generally clarify the distinction.
The dominant pattern is snake_case with a platform_prefix_resource suffix, and search_* consistently marks search operations. Minor deviations include noun-style names like amazon_best_sellers and place_photos, and the odd get_ skill/comments tools, but the overall convention is predictable.
74 tools is far beyond the typical well-scoped MCP server, even for a multi-platform API aggregator. The breadth is justified by the many platforms covered, but an agent will face a very large action space, and this could reasonably be split into per-platform servers.
The server provides strong lifecycle coverage for its read-only domain: search, profile/details, posts, and engagement data across most platforms. Gaps exist for some platforms (e.g. no LinkedIn person profile, no Facebook event details, no Truth Social profile/search, no Reddit subreddit-specific tools), but the core workflows are well covered.
