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Serpapi

by io.github.pipeworx-io

Serpapi Google Maps

serpapi_google_maps
Read-onlyIdempotent

Find local businesses on Google Maps for <query> — returns name, address, rating, reviews, phone, website, and GPS coordinates via SerpApi. Example: serpapi_google_maps({ q: "coffee shops", ll: "@40.7,-74.0,14z", _apiKey: "your-serpapi-key" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query, e.g. "coffee shops", "plumbers near me"
llNoOptional GPS location + zoom anchor, e.g. "@40.7,-74.0,14z" (latitude,longitude,zoom)
_apiKeyYesSerpApi API key (get one at serpapi.com)

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. Description adds that it returns specific fields but does not contradict annotations. No additional behavioral context beyond what annotations provide.

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?

Single sentence plus an example. Purpose is front-loaded, no wasted words. Highly efficient for a tool with 3 parameters.

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?

For a simple search tool with good annotations and no output schema, the description covers return fields and provides an example. Missing details on pagination or rate limits, but completeness is adequate for common use.

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%, so baseline is 3. Description includes an example with parameter values, but the schema already describes parameters thoroughly. Minimal extra meaning added beyond the schema.

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?

Clear verb+resource: 'Find local businesses on Google Maps'. Distinguishes from sibling tools like serpapi_google_jobs, serpapi_google_news, etc. by focusing on local business search and specifying return fields.

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?

Provides an example but no explicit guidance on when to use vs alternatives or when not to use. The context is implied (search local businesses), but lacks exclusions or comparison to other search tools.

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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TDQS

A3.8/5.0
Disambiguation3/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, deep_research, and bet_research all querying data but with nuanced differences. The descriptions help but boundaries remain fuzzy, especially between ask_pipeworx and deep_research for broad vs. single lookups. Overall moderate ambiguity.

Naming Consistency2/5

Naming is inconsistent: some tools use snake_case (ask_pipeworx, ai_visibility_check), others use camelCase (serpapi_google_jobs), and patterns vary widely (e.g., pipeworx_feedback vs. compare_entities). Only the serpapi_google_* group follows a consistent pattern.

Tool Count3/5

36 tools is on the high side for a single server, with many meta-tools (discover_tools, suggest_questions) and niche prediction market tools. The scope seems overly broad, covering data lookup, prediction markets, memory, and subscriptions, which could be streamlined to a more focused set.

Completeness3/5

The server covers a wide range of domains (financial, economic, news, drugs, prediction markets, Google services), but lacks direct web search and write/update capabilities. While the coverage is broad, there are notable gaps (e.g., no generic web search, limited tool for modifying data) for a data-focused server.

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