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mcp-knowledge

by io.github.getgapup

email_domain_health_check

Read-onlyIdempotent

Comprehensive email domain health check: MX routing, SPF authentication, DKIM signing, DMARC policy enforcement, DNSBL blacklist status (Spamhaus/SpamCop/Barracuda), TLS certificate validity, and WHOIS registration age. Aggregates a reputation score 0-100 and generates P0/P1/P2 deliverability signals. Accepts a domain (stripe.com) or email address (info@stripe.com). Detects role-based addresses (info@, support@, admin@, noreply@) that have higher bounce rates. Detects email provider (Google Workspace, Microsoft 365, Amazon SES, etc.). P0 signals: blacklisted / no MX / TLS expired / no SPF + DMARC none. P1 signals: SPF soft-fail / no DKIM selector / DMARC no reporting. P2 signals: role-based address / TLS expires <30d / domain age <90 days. All checks are keyless (no API keys required). Cache TTL 1h. SLA <=10s p95.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
emailNoFull email address for additional checks: format validity, role-based detection (e.g. "ceo@stripe.com").
checksNoSubset of checks to run. Defaults to all 8: ["mx","spf","dkim","dmarc","blacklist","whois","tls","reputation"]. Use a subset for faster responses (e.g. ["mx","spf","dmarc","reputation"] for quick scoring).
domainYesDomain to check (e.g. "stripe.com" or "@stripe.com"). If an email address is provided here, the domain is extracted automatically.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
mxYes
spfYes
tlsNo
dkimYes
dmarcYes
whoisNo
domainYes
statusYes
sourcesYes
blacklistYes
email_validNo
quality_scoreYes
reputation_scoreYes
email_is_role_basedNo
deliverability_signalsYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, consistent with the description. The description adds key behavioral traits: keyless operation, 1h cache TTL, 10s p95 SLA, and async mode via job_id polling. No contradiction.

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 paragraph but well-structured and front-loaded with the primary purpose. It could be more concise by using bullet points, but it efficiently packs a lot of information without redundancy.

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 (not shown but indicated), the description does not need to detail return values. It covers all crucial aspects: checks performed, usage notes, performance characteristics, and unique features (keyless). No gaps.

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

Parameters5/5

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

Schema coverage is 100%, and the description adds significant value beyond schema: explains async behavior, email parameter for additional checks (role-based detection), checks parameter with default and usage for faster responses, and domain parameter auto-extraction from email addresses. This enriches each parameter's meaning.

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 explicitly states 'Comprehensive email domain health check' and enumerates specific checks (MX, SPF, DKIM, DMARC, blacklist, TLS, WHOIS). It clearly distinguishes itself from siblings by its specialized focus; no other sibling tool overlaps with this exact functionality.

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 clearly indicates the tool is for email domain health assessment, but does not explicitly state when NOT to use it or mention alternatives. However, the specificity of the checks and the context of deliverability make it implicitly clear. The async parameter hint suggests usage for slow operations.

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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