mcp-drizly

get_product_details

Retrieve comprehensive product specifications including ABV, origin, ratings, and pricing for alcohol items on Drizly using a product identifier.

Instructions

Get detailed information about a specific product including ABV, origin, ratings, and pricing

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "productId": "<productId>"
    },
    "name": "get_product_details"
  }
}

Input Schema

Name	Required	Description	Default
`productId`	Yes	Product ID or slug from Drizly

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Mar 13, 2026

TDQS

B3.3/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the tool retrieves information (a read operation), but doesn't disclose behavioral traits such as authentication needs, rate limits, error conditions, or whether it requires a valid product ID format. This leaves significant gaps for an agent to understand how to invoke it safely and effectively.

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 a single, efficient sentence that front-loads the purpose and lists key attributes without unnecessary words. Every part of the sentence contributes to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is moderately complete for a simple read tool. It specifies what information is returned (ABV, origin, ratings, pricing), but lacks details on response format, error handling, or dependencies. For a tool with one parameter and high schema coverage, it's adequate but has clear gaps in behavioral context.

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?

The input schema has 100% description coverage, with the parameter 'productId' documented as 'Product ID or slug from Drizly'. The description adds no additional parameter semantics beyond what the schema provides, such as examples or format details. Baseline 3 is appropriate since the schema does the heavy lifting.

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 clearly states the verb 'Get' and resource 'detailed information about a specific product', with specific attributes listed (ABV, origin, ratings, pricing). It distinguishes from siblings like 'search_products' (which likely returns multiple products) and 'browse_categories' (which is category-based), though it doesn't explicitly name these distinctions.

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?

The description implies usage when detailed information for a specific product is needed, but doesn't explicitly state when to use this tool versus alternatives like 'search_products' (for broader searches) or 'get_recommendations' (for suggestions). No exclusions or prerequisites are mentioned.

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

Deploy Server