Tests a live website or local codebase to check if Web MCP (Streamable HTTP/SSE endpoint, manifest, or DOM tools) is enabled, runs protocol compliance diagnostics, and provides language-specific implementation code fixes.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Live website URL to test for Web MCP enablement (e.g. https://example.com). | |
| targetLanguage | No | Optional target programming language or framework to generate customized code fixes for. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It states that the tool runs tests and diagnostics and provides code fixes, which gives a reasonable picture. It does not disclose potential side effects such as network requests to the target site or whether generated fixes are actually applied, but the non-mutating language ('tests', 'provides') offers a baseline of transparency.
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 dense sentence that front-loads the main purpose ('Tests') and then efficiently lists the main outcomes. Every clause adds information, though it could be split into separate sentences for easier parsing.
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?
The description covers the core inputs and outputs well enough for an agent to select and invoke the tool, especially with a fully documented required parameter. However, there is no output schema, and the description does not explain what the diagnostics report contains or the relationship between 'local codebase' and the required 'live website URL' parameter.
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 coverage is 100%, so the baseline is 3. The description reinforces that targetLanguage is for language-specific fixes, matching the schema. It does not add much beyond the schema, and it introduces a slight ambiguity by mentioning 'local codebase' while the schema only documents a live website URL.
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 names a specific action ('Tests'), a clear resource ('live website or local codebase'), and a distinctive objective ('check if Web MCP ... is enabled'). It also mentions diagnostics and code-fix generation, which helps differentiate it from generic audit siblings. It does not explicitly name a sibling to distinguish from, but the unique Web MCP focus makes the purpose clear.
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 when to use the tool: when you need to verify Web MCP enablement or get compliance fixes. However, it does not provide explicit guidance on when not to use it or how it compares to related tools like seo_generate_code_fix or seo_audit_technical.
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 audit tools target distinct SEO dimensions, but several overlap: seo_audit_technical, seo_audit_robots_and_sitemap, and seo_audit_sitemap_multipage all involve robots.txt, sitemaps, and header checks. The descriptions help, but an agent could easily misselect between these related tools.
All tools follow a consistent seo_ prefix with clear verb_noun snake_case naming: audit_, crawl_, discover_, generate_, suggest_, test_, validate_. There is no mixing of conventions or vague generic verbs.
With 21 tools, the server sits in the 16-25 'heavy' range. The broad SEO scope justifies many of them, but the large number of overlapping audit variants makes the set feel slightly bloated.
The server covers the SEO lifecycle well: discovery, crawling, dimension-specific audits, full audits, code fixes, sitemap/robots generation, and validation. Minor gaps such as dedicated backlink or mobile usability audits exist, and the '8-dimension' full audit claim does not align with the 12 distinct audit tools.