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FeedDoctor MCP

FeedDoctor MCP

by anthonymorey
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

List Merchant Center Accounts & Stores

list_accounts
Read-onlyIdempotent

Lists accessible Google Merchant Center accounts and Microsoft Merchant Center stores, normalized to one schema, so you can discover account IDs before running feed diagnostics.

Instructions

Lists accessible Google Merchant Center accounts (Merchant API v1) and Microsoft Merchant Center stores (Bing Content API) normalized to one schema. Read-only and stateless.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_accounts"
  }
}

Input Schema

NameRequiredDescriptionDefault
platformNoWhich platform(s) to query: "google", "microsoft", or "both".both
credentialsNoOptional per-call credential overrides. If omitted, credentials are resolved from the HTTP Authorization Bearer token / headers or self-host environment variables.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so safety is covered; the description's 'read-only and stateless' largely restates that. It does add value with 'normalized to one schema' and the two upstream API versions, but says nothing about behavior when credentials are absent/invalid or how partial failures are handled when platform='both'.

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?

Two sentences, front-loaded with the resource and scope, with the return-normalization note second. No filler and nothing an agent must read past to find the core action.

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?

There is no output schema, and 'normalized to one schema' plus the two named upstream APIs is a reasonable proxy for what comes back, so the description is nearly complete for a simple discovery tool. A brief hint on per-platform error or empty-result behavior is the only real gap, offset by fully documented parameters and rich annotations.

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 both top-level parameters (the platform enum and the nested credentials override object) are documented in-schema, including scopes and fallback resolution. The description adds no extra meaning about default behavior (platform defaults to 'both') or the credential-override mechanism, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb (Lists) and concrete resources (Google Merchant Center accounts via Merchant API v1, Microsoft Merchant Center stores via Bing Content API), plus the normalization detail. It is clearly distinct from the product/feed-focused siblings, though it never names an alternative to disambiguate.

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?

Usage is only implied: 'accessible' accounts suggests a discovery/setup step that would precede tools like feed_health_summary or diagnose_product. There is no explicit when-to-use, when-not-to-use, or prerequisite statement (e.g., call this first to obtain account IDs).

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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