gapup-mcp

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

Name	Required	Description
`async`	No	If 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.
`email`	No	Full email address for additional checks: format validity, role-based detection (e.g. "ceo@stripe.com").
`checks`	No	Subset 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).
`domain`	Yes	Domain 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

Name	Required	Description	Default
`mx`	Yes
`spf`	Yes
`tls`	No
`dkim`	Yes
`dmarc`	Yes
`whois`	No
`domain`	Yes
`status`	Yes
`sources`	Yes
`blacklist`	Yes
`email_valid`	No
`quality_score`	Yes
`reputation_score`	Yes
`email_is_role_based`	No
`deliverability_signals`	Yes

TDQS

A4.2/5.0

Behavior5/5

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

The description fully discloses behavioral traits beyond annotations: it details all 8 checks, P0/P1/P2 signal definitions, detection of role-based addresses and email providers, async behavior, caching, and SLA. Annotations only provide readOnlyHint, openWorldHint, idempotentHint; the description adds rich operational context.

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 comprehensive but well-structured: it starts with the main purpose, lists checks, explains signals, then covers parameters and operational details. It is slightly long but every sentence adds value, and it is front-loaded with the core purpose.

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 tool's complexity and the presence of an output schema, the description is complete. It explains all inputs, outputs, behavior (async, caching, SLA), and the meaning of signals. The agent has sufficient context to 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 parameter descriptions in the schema already cover the details. The tool description adds no new information about parameters beyond what is in the schema; it only reiterates. However, it does provide overall output semantics (score, signals) which aids parameter understanding indirectly.

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's purpose: comprehensive email domain health check including MX, SPF, DKIM, DMARC, blacklist, TLS, WHOIS, and reputation scoring. It specifies verb 'health check' and resource 'email domain', and distinguishes from siblings by focusing on email deliverability.

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

Usage Guidelines3/5

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

The description implies usage for checking email domain health and mentions keyless operation, caching, and SLA, but does not explicitly state when to use this tool over alternatives or provide exclusions. It lacks explicit when-not guidance.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

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