stack-and-dns-mcp

Comprehensive Domain Audit

comprehensive_audit

Read-onlyIdempotent

Run web tech-stack and email infrastructure checks together, then combine deliverability, security, and DNS maturity into a 0-100 health score with a letter grade and ranked findings.

Instructions

Run inspect_tech_stack and verify_email_infrastructure concurrently and aggregate them into a single 0-100 health score (email deliverability 40%, security posture 35%, infrastructure maturity 25%) with a letter grade, merged severity-sorted findings, and human-readable highlights suitable for a research brief or CRM enrichment. Includes the full output of both underlying tools. If one inspection fails the other still completes and the error is reported inline. Cost: 2 credits.

Input Schema

Name	Required	Description
`domain`	Yes	Domain to inspect. Accepts a bare hostname ("example.com"), a URL ("https://www.example.com/pricing") or an email address ("jane@example.com"). Scheme, path, port and query are stripped; IDN names are accepted.
`dkimSelectors`	No	Extra DKIM selectors to probe.
`includeEvidence`	No	Include detection evidence snippets in the tech-stack section.
`includeRawHeaders`	No	Include the raw response header map in the tech-stack section.

Output Schema

Name	Required	Description	Default
`email`	Yes
`domain`	Yes
`scores`	Yes
`billing`	Yes
`summary`	Yes
`timings`	Yes
`findings`	Yes
`auditedAt`	Yes
`techStack`	Yes
`emailError`	Yes
`highlights`	Yes
`inputDomain`	Yes
`findingCounts`	Yes
`techStackError`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Nov 4, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Goes well beyond the readOnly/idempotent/non-destructive annotations: it discloses partial-failure semantics ('if one inspection fails the other still completes and the error is reported inline'), the credit cost, the exact score composition, and what the response aggregates. Those are precisely the behaviors an agent cannot infer from the annotation set.

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?

Front-loaded with the verb and the composition, then three short clauses that each add non-redundant information: aggregation details, partial-failure behavior, and cost. No restatement of the title and no filler.

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

Completeness4/5

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

For a composite tool with an output schema, the description covers composition, weighting, failure behavior, and cost — everything needed to invoke and interpret it. The only mild gap is not explaining whether the returned sub-tool outputs can be used to re-derive or override the aggregate score.

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 each of the four parameters carries its own descriptive text, so the schema already does the work. The description adds no meaning about the parameters themselves (e.g. how dkimSelectors affects the email score), leaving this at the baseline for a fully documented schema.

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?

States a specific action chain (run inspect_tech_stack and verify_email_infrastructure concurrently, aggregate into a single 0-100 score), names both underlying sibling tools, and spells out the weighting model. An agent can distinguish this composite tool from the two single-purpose siblings without opening any schema.

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 makes clear this is the composite alternative to calling the two underlying inspections separately ('Includes the full output of both underlying tools') and names concrete use cases (research brief, CRM enrichment), plus a cost signal of 2 credits that helps an agent choose the cheaper single-tool path. It stops short of an explicit 'do not use when you only need the tech stack' exclusion.

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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