Skip to main content
Glama
sepehr071

snapp-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Grocery store reviews

market_reviews
Read-onlyIdempotent

Check a store's 30 relevant customer comments and ratings before recommending it. Optionally return full comment text for quality assessment.

Instructions

Read a store's 30 most relevant customer comments, rating 0-5.

Use as a quality check before recommending a store. No paging: the API returns the same 30 comments.

Input Schema

NameRequiredDescriptionDefault
full_textNoReturn comment text uncut (default cut to 400 chars).
vendor_codeYesStore code from market_search / market_stores, e.g. '32xxwe'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.2.0
    • addedInput schema / properties / full_text
      Added value: +{
+  "default": false,
+  "description": "Return comment text uncut (default cut to 400 chars).",
+  "type": "boolean"
+}
    • removedInput schema / properties / vendor_code / title
      Removed value: -"Vendor Code"
    • removedInput schema / title
      Removed value: -"market_reviewsArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "market_reviewsDictOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.1

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare this a safe, idempotent read. The description adds genuinely new behavioral facts: the result set is capped at 30 comments, there is no paging, and repeated calls return the same set — all useful for deciding whether the tool is worth calling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, with the core operation front-loaded ahead of the usage hint. The trailing 'rating 0-5' phrase is slightly ambiguous (rating field range vs. overall score) but costs little.

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?

With no output schema, the description responsibly describes the return shape (30 comments with ratings) and the fixed result-set behavior. An agent has enough to call it and interpret results, though the rating-range phrasing could be clearer.

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%, so both parameters are fully documented in the schema. The description adds only the rating scale (0-5) and the 30-comment cap, which does not materially extend what the schema already conveys.

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 states a specific verb and resource ('Read a store's 30 most relevant customer comments'), which is far more precise than the title alone. It implicitly separates itself from food_reviews by scoping to stores, but never names that sibling to make the distinction explicit.

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?

'Use as a quality check before recommending a store' gives a concrete decision context for invoking the tool. It offers no exclusions or comparison against the restaurant-review sibling, so it falls short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools