If the user has linked GA4 + Google Search Console, return the 28-day organic traffic snapshot for an audit: session count, daily trend, top landing pages, top queries, and indexing health. Returns connected: false if Google is not linked. Cached 24h server-side. Requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
| audit_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full transparency burden. It discloses the connected:false error condition, caching behavior (24h server-side), and API key requirement. This goes beyond the schema and gives useful 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and includes necessary caveats without unnecessary fluff. Every sentence adds value.
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?
The description covers the main output data, error conditions, caching, and authentication. While there is no output schema, the listed data points give a good sense of the return value. It does not describe the exact format or pagination, but for a snapshot tool this is adequate.
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 description coverage is 0% for the single parameter audit_id, and the description never explicitly explains what audit_id is or how to obtain it. The purpose is inferable from the tool name and context, but the description does not compensate for the lack of schema documentation.
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 returns a 28-day organic traffic snapshot for an audit, listing specific data points (session count, daily trend, top landing pages, top queries, indexing health). This distinguishes it from sibling tools like get_audit or run_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 provides a clear prerequisite (GA4 + Google Search Console linked) and specifies it is for audits. However, it does not explicitly identify when to use this tool over alternatives or mention exclusions, so it falls short of a perfect score.
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.
Each tool targets a distinct resource or action: get_audit retrieves JSON findings, get_audit_pdf fetches a PDF, list_audits enumerates prior audits, run_audit queues an authenticated audit, run_audit_anonymous runs a sync anonymous audit, and get_organic_traffic provides Google-linked analytics. The two audit-running tools are clearly differentiated by auth and synchronicity, and the descriptions explicitly contrast them.
All tool names follow a consistent verb_noun snake_case pattern: get_*, list_*, run_*. The two run tools share the same verb with a descriptive suffix (_anonymous), maintaining a predictable and readable convention.
Six tools is well within the ideal 3-15 range for an SEO audit MCP. Each tool serves a distinct phase of the audit workflow (trigger, retrieve, list, report, analytics), earning its place without redundancy.
The tool set covers the full audit lifecycle: initiating audits (both anonymous and authenticated), retrieving results, listing historical audits, generating PDF reports, and accessing traffic analytics. No obvious gaps exist; the domain is fully addressed for a read-centric audit API.
