youtube-title-generatorYouTube Title & Description Generator: Write a YouTube title, description, and tags for a video topic. (free, AI-generated, rate-limited).
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds value by noting the tool is 'free, AI-generated, rate-limited.' This provides behavioral constraints (rate limits) and output nature (AI-generated) beyond annotations. It does not thoroughly explain output structure, but given annotation coverage, the added context is useful.
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?
The description is a single, focused sentence plus a concise parenthetical. It front-loads the tool's name and then explains the function in one clause. Every word contributes to understanding the tool's purpose and constraints, with no filler or redundancy.
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 simple one-parameter tool with no output schema, the description is largely complete. It states the function, the input role, and key behaviors (free, rate-limited). It does not specify the return format, but the description implies the output includes title, description, and tags. This is sufficient for a low-complexity tool.
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?
Schema has 0% description coverage for the sole parameter 'topic'. The description partly compensates by stating 'for a video topic,' implying the input is the video topic. However, it does not elaborate on format, examples, or how the topic influences the output. The description provides minimal added meaning beyond the schema field name.
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?
Description clearly states the tool's function: 'Write a YouTube title, description, and tags for a video topic.' It uses a specific verb (Write) and identifies the resource (YouTube title, description, tags) and context (video topic). This distinguishes it from sibling tools like seo-title-generator or meta-description-generator.
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 provides clear context for when to use: when you have a video topic for YouTube content. It indicates the tool is for YouTube-specific metadata, but does not explicitly mention exclusions or alternatives. The phrase 'for a video topic' implies usage, though it lacks direct references to sibling tools.
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 have distinct purposes, but word-counter and character-counter overlap heavily, and meta-tag-generator subsumes several other generators (title, description, canonical). The sheer number of adjacent content generators creates some ambiguity, though descriptions generally clarify.
Tool names are inconsistent: some use snake_case (create_site, get_article, list_articles) while others use hyphenated lowercase (ad-copy-generator, meta-tag-generator, robots-txt-generator). This mixing of conventions makes it hard for an agent to predict the name for a given action.
With 59 tools, the server is heavily over-scoped for a typical MCP server. Many tools are similar (various calculators, many content generators) and could be consolidated, making the surface bloated and harder to navigate.
The server covers a broad range of SEO tasks: site management, article generation/publishing, analytics, technical SEO, and content tools. However, there are gaps such as missing update/delete operations for articles and no backlink analysis, leaving some workflows incomplete.