[Google Maps] Search Google Maps for local businesses. Returns business names, addresses, ratings, phone numbers, and websites.
Args: query: Business type or search query (e.g. 'plumber', 'italian restaurant') location: City or area to search (e.g. 'San Francisco, CA') max_results: Maximum results (default 20)
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| location | Yes | ||
| max_results | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description does not add behavioral details beyond what annotations provide, such as authentication, rate limits, or what happens on errors. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences plus a concise Args section. Every sentence adds value: purpose, return fields, examples, and parameter explanation. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with three parameters and no output schema, the description covers purpose, inputs, and outputs adequately. It could mention pagination or limitations (e.g., only US locations?), but overall it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It gives example values for query and location ('plumber', 'italian restaurant', 'San Francisco, CA') and explains max_results ('Maximum results (default 20)'), adding meaning beyond the schema's type definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Google Maps for local businesses' and enumerates return fields (names, addresses, ratings, etc.), making the purpose unambiguous. It distinguishes from sibling tools like generate_leads and validate_emails by focusing on search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides example inputs for query and location but offers no guidance on when to use this tool versus alternatives (e.g., generate_leads). There is no mention of use cases, exclusions, or context where another sibling would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping functionality across categories (e.g., multiple search_arxiv, search_google_scholar, real estate tools, DNS/WHOIS checks). An agent would struggle to differentiate between similar tools from different categories, leading to ambiguity.
Tools follow a 'category__verb_noun' pattern mostly, but verbs vary (get, search, screen, check, etc.) and some categories use different orders (e.g., 'get_repo_stats' vs 'search_repos'). The consistency is acceptable but not uniform across the entire set.
With 152 tools, the server is excessively large for a single MCP server. While it aims to be an all-in-one gateway, the sheer number overwhelms the agent and likely exceeds practical limits for coherent selection.
The server covers a wide range of domains (finance, real estate, news, developer tools, etc.) but has notable gaps (e.g., social media APIs, CRM tools). Coverage is broad but not exhaustive, and some niche areas (e.g., global stock exchanges) are over-represented.