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backlinkmcp-server

by io.github.johnsmalls22-rgb

flag_toxic_links

Toxic / low-quality backlink audit: scans a domain's LINKERS and flags spammy disavow CANDIDATES — abused TLDs (.tk/.xyz/.loan…), spam keywords in the domain, hyphen/keyword stuffing, and link-farm-level outbound counts. The inverse of find_link_prospects. Domain-level heuristic only (no per-link URL/anchor), so each row is a DOMAIN worth REVIEWING, never a confirmed toxic link. Note: Google says most sites should NOT disavow — use this to audit, not to auto-disavow. Free returns up to 25 flags, Pro up to 100.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesThe domain whose inbound links you want to audit for toxic/spam linkers, e.g. 'yoursite.com'.

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden, and it delivers: it discloses that results are heuristic candidates, never confirmed toxic links, and explains the row-level granularity. It also conveys practical constraints like Google's disavow guidance and free/Pro return limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet information-dense. It front-loads purpose, follows with scope limitations, then cautions and quota. Each sentence adds distinct value with no filler.

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 absence of annotations and output schema, the description fully covers what the tool returns (flagged domain candidates), what it does not do (no per-link analysis), and the operational context (audit vs disavow, result limits). An agent has what it needs to select and invoke 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 description coverage is 100%, so the baseline is 3. The description reinforces that 'domain' refers to the domain whose inbound linkers are scanned, but it adds little beyond the schema's own wording.

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 opens with a specific verb ('audit') and resource ('a domain's LINKERS'), then details exactly what is flagged and how. It also differentiates itself from the sibling tool find_link_prospects by stating it is the inverse, and clarifies it is domain-level, not per-link.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names find_link_prospects as the inverse alternative, and tells the agent to 'use this to audit, not to auto-disavow.' This provides a clear when-to-use and when-not-to-use directive that an agent can act on.

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

A4/5.0
Disambiguation4/5

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.

Naming Consistency3/5

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.

Tool Count5/5

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.

Completeness4/5

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.

Resources