Get an editorial-authority score for a domain (weighted toward high-trust wiki/edu/gov/news referrers, from BacklinkMCP's proprietary web-scale link index). Returns a domain_rating-style score plus referring domain count.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Root domain, e.g. 'stripe.com'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It clearly explains the data source (BacklinkMCP's proprietary web-scale link index), the scoring emphasis, and the return values (domain_rating-style score plus referring domain count). It does not mention rate limits, freshness, or explicit read-only status, but the 'Get' verb and described output provide meaningful behavioral context.
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 two dense sentences with no wasted words. The core purpose is front-loaded, followed by useful methodological context and return-value information. Every sentence contributes to the agent's understanding.
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 single-parameter read-style tool with no output schema, the description gives sufficient information to invoke it correctly: what it returns, how the score is weighted, and what data source is used. Slightly more detail about the exact output shape or acceptable domain format would make it fully complete, but it is already adequate.
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 100%, and the single parameter 'domain' is already documented with an example in the schema. The description adds little beyond the schema, only reinforcing that the score is per-domain, so the baseline score of 3 is appropriate.
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 verb ('Get'), a clear resource ('editorial-authority score for a domain'), and distinguishes the tool by explaining its weighting toward high-trust wiki/edu/gov/news referrers. This makes it easy to tell apart from sibling tools focused on backlink lists or audits.
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 does not say when to choose this tool over alternatives such as backlinks_for_domain, top_linkers_for_domain, or common_linkers. It implies a use case (evaluating domain authority) but provides no explicit when/when-not guidance or 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 target distinct actions, but backlinks_for_domain and top_linkers_for_domain overlap significantly since both return ranked linking domains with authority and link counts, differing mainly in scope. The descriptions do clarify one is a full payload and the other a quick skim, so an agent can usually choose correctly.
All names are lowercase snake_case and readable, but conventions are mixed: several are noun phrases like site_audit and domain_authority_score, some are verb-first like find_link_prospects, and a couple are object-verb like schema_validate and indexnow_submit. The set is understandable but lacks a single consistent naming pattern.
13 tools is appropriate for a backlink and SEO-focused server, fitting comfortably in the well-scoped range. Each area—backlink analysis, AI visibility, site auditing, and indexing—has dedicated tools without the set feeling bloated.
The backlink workflow is well covered: scoring, listing, overlapping linkers, prospect discovery, toxic-link flags, and live verification all exist. Minor gaps remain, such as no per-URL or anchor-level backlink data and no rank-tracking or keyword research, but the core stated purpose is served without major dead ends.