Check live SPF, DKIM, and DMARC DNS records for a domain and report alignment problems with the exact record to publish. Works for any domain, not only your own.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to check, e.g. example.com |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds context beyond annotations by noting the check is 'live,' and that it 'report[s] alignment problems with the exact record to publish.' This provides actionable insight into what the tool does with the data it fetches, which is not covered by annotations.
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 sentences long, front-loads the core purpose, and contains no filler or redundancy. Every sentence contributes critical information: what records are checked, what is reported, and scope of applicability.
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 simple read-only tool with full annotations and a single parameter, the description is largely complete. It covers the DNS record types checked, the output (alignment problems and publishable record), and domain scope. The absence of an output schema is acceptable since the description adequately describes what the tool returns.
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 coverage is 100% with a single parameter described as 'Domain to check, e.g. example.com.' The description adds value by stating 'Works for any domain, not only your own,' which clarifies that the domain parameter is not restricted to the user's own domains—a meaningful addition beyond the schema description.
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 clearly states the tool checks live SPF, DKIM, and DMARC DNS records for a domain and reports alignment problems with the exact record to publish. It uses specific verbs ('Check', 'report') and identifies the resource (DNS records for a domain), distinguishing it from sibling tools like verify_domain or run_deliverability_audit.
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 states 'Works for any domain, not only your own,' clarifying domain scope and implying broad applicability. However, it does not explicitly mention when to use this tool versus alternatives (e.g., verify_domain), nor does it provide any 'when not to use' guidance or prerequisites.
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 are cleanly separated by resource and action, and the descriptions do a good job of cross-referencing related tools. However, there are several close clusters—get_analytics vs generate_report, get_deliverability_score vs run_deliverability_audit, check_dmarc vs verify_domain, and list_emails vs list_inbox_conversations vs get_email—that could cause an agent to pick the wrong one. The detailed descriptions reduce but do not eliminate this ambiguity.
Tool names follow a consistent snake_case verb_noun pattern throughout: create_, get_, list_, send_, toggle_, and so on. Even multi-word actions like select_ab_test_winner and categorize_inbox_emails stay uniform. The only slight deviation is the bare verb upgrade, but it is readable and does not break the overall pattern.
54 tools is far beyond the typical well-scoped MCP surface and lands heavily in the 'too many' range. While the domain is broad, many tools could be consolidated—multiple analytics/reporting tools, several deliverability checks, and separate email/inbox listing tools create redundancy. The sheer number increases selection overhead and makes the toolset harder for an agent to navigate reliably.
The core email marketing lifecycle is represented: domains, contacts, campaigns, templates, automations, sends, and analytics all have main operations. However, there are notable gaps—no update/delete for campaigns, templates, forms, or automations; no create/update/delete for forms; no sandbox enable/disable; and no way to install marketplace items. These are workable gaps but would cause failures for agents trying to perform full lifecycle management.