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Mrshahidali420

Google Search Console MCP Server

gsc_doctor

Diagnose Google Search Console MCP setup failures with five checks (OAuth, token, config, store, properties) and receive concrete next-step fixes for each issue.

Instructions

Diagnose whether gsc-mcp is set up to talk to Search Console.

Runs five checks in order — oauth_client, token, config, store, properties — and reports all of them even if one raises. A check that raises is recorded as ok: False with the exception's TYPE NAME only in detail; the message is never included, because it can carry a bearer token, a credentialed URL, or a raw response body. Every failing check carries a non-empty fix string with a concrete next step; this tool diagnoses, it does not repair anything itself.

Costs at most one Search Console API call (sites.list, for the properties check) — zero network calls if an earlier check already shows the client or token is unusable and a caller stops before reaching it, though this implementation always runs all five.

Returns {"ok": bool, "checks": [{"name", "ok", "detail", "fix"}, ...]}; ok is true only when every check passed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully discloses behavior: it runs five checks in order, reports all results even if one raises, omits exception messages for security, provides fix strings, and makes at most one API call. It even explains when zero network calls occur. This is exceptionally transparent.

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?

Though the description is multi-paragraph, every sentence earns its place—covering purpose, execution order, security filtering, fix strings, API cost, and return structure. The front-loaded purpose sentence ensures immediate clarity, and the format is well organized.

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?

The description is fully self-contained for a diagnostic tool: it explains the checks run, the exact return JSON shape, what determines overall success, and the side-effect/API cost. Given there is no output schema, the description covers everything an agent needs to invoke and interpret results.

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

Parameters4/5

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

The tool has zero parameters, and the input schema is empty. Baseline for 0 params is 4. The description adds no parameter meanings (none exist), and this is perfectly adequate since there is nothing to explain.

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 opens with a specific verb and resource: 'Diagnose whether gsc-mcp is set up to talk to Search Console.' This clearly distinguishes it from sibling tools like gsc_list_sites or gsc_check_status, as it targets setup and configuration health rather than data retrieval or status queries.

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 tool's usage context is clear: it is a diagnostic for setup, not a repair tool. It explains that it diagnoses and does not repair anything, which sets expectations. However, it does not explicitly compare itself to sibling tools or state when to prefer it over alternatives like gsc_check_status, so it stops short of full alternatives 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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