seo-geo-mcp-server

JavaScript Rendering Check

render_check

Read-onlyIdempotent

Check whether a page's content is server-rendered or JavaScript-dependent, detecting SPA shells to confirm AI assistants can access it.

Instructions

Determine whether a page's content exists in the server HTML, or only appears after JavaScript runs.

This matters more for AI visibility than for classic SEO: Googlebot renders JavaScript, but GPTBot, ClaudeBot, PerplexityBot and CCBot largely do not. A client-rendered page can rank perfectly well in Google and still be completely invisible to every AI assistant — this tool is how you catch that.

Detects unhydrated SPA shells (empty #root / #app / #__next containers), reports how many words survive without JS, and flags documents dominated by inline script bytes.

Args:

url (string): the page to check.
response_format ('markdown' | 'json'): output format (default 'markdown').

Returns: { renders_without_js, server_text_words, script_bytes, html_bytes, spa_shell_detected, framework_hint, findings[] }.

Example: "Can ChatGPT actually read https://example.com/app?" -> render_check(url="https://example.com/app").

Input Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes	Page URL to analyse, e.g. 'https://example.com/blog/post'. The scheme defaults to https://.
`response_format`	No	Output format: 'markdown' for a human-readable summary (default) or 'json' for the full structured payload.	markdown

Output Schema

TableJSON Schema

Name	Required	Description	Default
`findings`	Yes
`html_bytes`	Yes
`script_bytes`	Yes
`framework_hint`	Yes
`server_text_words`	Yes
`renders_without_js`	Yes
`spa_shell_detected`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv1.2.0Sep 16, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

removedInput schema / additionalProperties
```
Removed value: -false
```

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

First observedv1.0.0Aug 3, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds specific behavioral details such as detecting SPA shells, counting server-side words, and flagging script-heavy pages. It also describes the return fields, enriching beyond the annotations without contradicting them.

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 well-structured and front-loaded with the core purpose, followed by context, arguments, and returns. While it is somewhat lengthy, every sentence contributes to understanding, and the structure aids scanning.

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

Completeness4/5

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

For a tool with an output schema and safety annotations, the description covers purpose, usage context, parameters, and return format, including an example. It lacks edge-case handling or error details, but these are not essential given the available structured data.

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%, so both url and response_format are documented. The description reinforces the meaning of response_format, provides the default, and gives a concrete example mapping a natural-language query to the tool call, adding value beyond the schema.

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 determines whether content is server-rendered or appears only after JavaScript runs, and explicitly contrasts this with classic SEO concerns. It distinguishes itself from siblings like robots_txt_check and ai_crawler_access by focusing on rendering rather than access or crawling.

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?

It explains when the tool matters (AI visibility over classic SEO) and gives an example query, implying when to use it. However, it does not explicitly name alternatives or state when NOT to use it, though the context is sufficient given the sibling list.

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

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