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mcp-knowledge

by io.github.getgapup

seo_cro_audit

Read-only

Full SEO + CRO audit of any public URL. Analyses technical SEO (HTTP status, HTTPS, title/meta/canonical/robots, H1-H2, JSON-LD structured data, sitemap, robots.txt, OG/Twitter cards), content SEO (word count, keyword density top-10, readability estimate, image alt coverage, internal/external links), performance signals (page size, estimated render time, inline scripts/styles, unoptimised images), and CRO (CTA detection, above-fold CTAs, forms, social proof, trust signals, pricing visibility). Optionally compares up to 5 competitor URLs. Returns 0-100 scores per dimension plus a prioritised (P0/P1/P2) recommendation list. ICP: marketing managers, SEO/CRO consultants, e-commerce ops, agency teams. Budget: 8s per URL. Cache TTL: 1h.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFully-qualified URL to audit (e.g. https://stripe.com/pricing)
modeNoAudit scope — defaults to 'full'
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
compare_competitorsNoOptional list of competitor URLs to compare (max 5)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
statusYes
sourcesYes
audit_modesYes
content_seoYes
cro_signalsYes
quality_scoreYes
technical_seoYes
overall_scoresYes
recommendationsYes
performance_signalsYes
competitor_comparisonNo

TDQS

A4.4/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint), the description adds valuable behavioral details: performance budget (8s per URL), cache TTL (1h), output format (0-100 scores per dimension, prioritized recommendations). No contradictions with annotations.

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 a single comprehensive paragraph that front-loads the purpose followed by details and practical constraints. While thorough, it could be slightly more concise, but every sentence contributes to understanding.

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

Completeness5/5

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

Given the presence of an output schema and rich annotations, the description covers all necessary aspects: purpose, scope, parameters, behavioral traits, performance constraints, and target audience. It is fully adequate for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds little beyond what the schema already provides. It mentions defaults (e.g., mode defaults to 'full') and describes async behavior, but these are minor additions. The baseline of 3 is appropriate.

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 states it performs a 'Full SEO + CRO audit of any public URL' and lists specific technical, content, performance, and CRO areas. It clearly distinguishes itself from siblings like seo_keyword_research and competitive_deep_dive by focusing on URL-level audit across multiple dimensions.

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?

The description provides clear context by mentioning optional competitor comparison and the ability to limit scope via the mode parameter. It also identifies target user personas. However, it does not explicitly state when to avoid this tool or suggest alternatives among siblings.

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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TDQS

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

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