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Kroger

by io.github.pipeworx-io
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Kroger Store Locator

kroger_store_locator
Read-onlyIdempotent

Find Kroger-family grocery stores and supermarkets near a US ZIP code — covers Kroger, Ralphs, Fred Meyer, King Soopers, Fry's, Harris Teeter, QFC, Smith's, Dillons, Food 4 Less, Mariano's and more. Returns store names, addresses, phone, hours, and the location_id needed for price lookups. Example: kroger_store_locator({ zip_code: "45202" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoOptional chain filter, e.g. "Kroger", "Ralphs", "Fred Meyer"
limitNoMax stores to return, 1-50 (default 5)
_apiKeyNoOptional: your own Kroger API credentials as "client_id:client_secret" (free at developer.kroger.com)
zip_codeYesUS ZIP code to search near, e.g. "45202"
radius_milesNoSearch radius in miles, 1-100 (default 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "zip_code": "45202"
+  },
+  {
+    "chain": "Ralphs",
+    "limit": 10,
+    "radius_miles": 15,
+    "zip_code": "90210"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds value by specifying the return fields (names, addresses, phone, hours, location_id) and explaining that location_id is needed for price lookups, as well as noting the optional API key parameter. This covers behavioral context beyond annotations.

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?

The description is two sentences with an example, front-loading the purpose and key details. Every sentence earns its place, with no extraneous information.

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?

Given no output schema, the description covers the primary return fields (store names, addresses, phone, hours, location_id). It explains the tool's core functionality well. However, it does not mention error handling, pagination, or default behavior when parameters are omitted, which would be minor enhancements.

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 description coverage is 100% with all 5 parameters described. The description adds an example call but does not provide additional semantic meaning beyond what the schema already gives. The mention that 'location_id' is needed for price lookups is helpful but is not parameter-specific.

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 uses a specific verb ('Find') and clearly identifies the resource ('Kroger-family grocery stores and supermarkets') with a comprehensive list of banners. It distinguishes from sibling tools like 'kroger_product_details' and 'kroger_product_search' by focusing on store locator functionality.

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 states the tool is for finding stores near a US ZIP code. It provides an example call. However, it does not explicitly state when to use this tool versus alternatives or mention when not to use it. The context is clear enough given sibling names.

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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