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Yelp

by io.github.pipeworx-io
OverviewDiscussionsAdmin

Get Business

get_business
Read-onlyIdempotent

Get full details for a single Yelp business by its id or alias. Returns rating, review count, price, categories, address, phone, hours, photos, and coordinates. Example: get_business({ id: "garaje-san-francisco" }).

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "garaje-san-francisco"
    },
    "name": "get_business"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesYelp business id or alias (from search_businesses results).
_apiKeyNoRequired — your own Yelp Fusion key. Pipeworx fronts no platform key for Yelp (Fusion plan is $229/mo, #2275 open); every call is refused with none.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / _apiKey / description
      Previous value: -"Optional — your own Yelp Fusion API key for higher limits; omit to use the shared Pipeworx key."New value: +"Required — your own Yelp Fusion key. Pipeworx fronts no platform key for Yelp (Fusion plan is $229/mo, #2275 open); every call is refused with none."
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": "garaje-san-francisco"
+  },
+  {
+    "id": "WavvLdfdP6g8aZTtbBQHTw"
+  }
+]
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds behavioral context by listing the response contents (rating, review count, price, hours, coordinates, etc.), going beyond the structured metadata. It does not discuss edge cases like missing fields or quota limits, but that is not necessary given the annotation coverage.

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 tight sentences plus a concrete example. The main action and resource are front-loaded, and every clause adds value: the returns list tells the agent exactly what to expect)Skip. There is no filler or repetition of schema details.

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?

Despite having no output schema, the description enumerates the important response fields, making the return shape predictable. With only one required parameter, a clear example, and annotations covering safety, an agent has everything needed to call this tool correctly.

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%: both id and _apiKey are fully documented in the input schema, including the alias source and the mandatory API key requirement. The description contributes an example value but no additional parameter semantics, so the baseline of 3 is appropriate.

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 starts with a specific verb and resource: 'Get full details for a single Yelp business by its id or alias.' It also lists the returned fields (rating, review count, price, categories, etc.), which clearly distinguishes it from sibling tools like search_businesses and get_reviews. The example further solidifies the intent.

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 implies the tool is for fetching details for one known business, and the schema notes the id comes from search_businesses results, providing clear context. However, it does not explicitly name alternative tools or state when not to use this one, so it misses the explicit exclusion that would earn a 5.

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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