schema-generatorBuild valid JSON-LD structured data (FAQ, Article, Organization, or Product) for rich results.
| Name | Required | Description | Default |
|---|---|---|---|
| faqs | No | ||
| type | Yes | ||
| article | No | ||
| product | No | ||
| organization | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds the supported types and the 'valid' guarantee. However, it does not disclose the return format, validation behavior on invalid input, or how the structured data is delivered, leaving some transparency gaps.
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 sentence of about 16 words, front-loading the purpose and supported types. Every word earns its place, with no fluff.
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?
Given five parameters, one required, with nested objects and no output schema, the description is too brief. It omits parameter relationships, expected outputs, and error handling, making it incomplete for practical invocation.
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 description coverage is 0%, and the description only restates enum values already present in the schema. It fails to explain the structure of faqs, article, product, or organization parameters, providing no added meaning beyond the input schema.
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 clearly states the tool builds JSON-LD structured data with specific types (FAQ, Article, Organization, Product), matching the enum. This specific verb and resource scope differentiates it from sibling content generators, making its purpose unambiguous.
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 no guidance on when to use this tool versus alternatives, such as faq-generator or other markup generators. It merely states the action without context, prerequisites, or exclusions.
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.