List supported Google Maps place type values for search filters.
Returns place_types as a string array. Use a value with place_type on google-maps.search or google-maps.nearby_search.
Cost = 1 token.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| place_types | No | Supported Google Maps place type string values. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / $defsRemoved value: -{
- "GoogleMapsPlaceTypesResponsePlaceTypesItem": {
- "additionalProperties": true,
- "properties": {
- "place_type": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "Place type value (for example restaurant).",
- "title": "Place Type"
- }
- },
- "title": "GoogleMapsPlaceTypesResponsePlaceTypesItem",
- "type": "object"
- }
-}Output schema / properties / place_types / anyOfPrevious value: -[
- {
- "items": {
- "$ref": "#/$defs/GoogleMapsPlaceTypesResponsePlaceTypesItem"
- },
- "type": "array"
- },
- {
- "type": "null"
- }
-]New value: +[
+ {
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ {
+ "type": "null"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It states the return type ('Returns place_types as a string array') and cost ('Cost = 1 token'), which is useful. However, it does not mention potential limitations such as whether the list is exhaustive or sorted, but for a simple list tool this is adequate.
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 three sentences long, front-loaded with the main purpose, and every sentence earns its place. It covers purpose, return type, usage, and cost without any filler.
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, zero-parameter tool with an output schema, the description is complete. It explains what the tool does, what it returns, how to use the results, and the cost. No further information is needed.
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?
The tool has zero parameters, so the baseline is 4. The description adds no parameter details because none exist, but it explains how the returned values will be used as parameters in other tools (place_type), which adds practical value beyond the empty schema.
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 the tool's purpose: 'List supported Google Maps place type values for search filters.' It uses a specific verb (List) and resource (Google Maps place type values), distinguishing it from sibling search tools like google-maps.search and google-maps.nearby_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 explicitly says when to use the tool: 'Use a value with place_type on google-maps.search or google-maps.nearby_search.' This direct guidance tells the agent exactly how to apply the results, which is clear and actionable.
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.
Each tool has a distinct purpose, further clarified by group prefixes and clear descriptions. Within each group, tools perform different operations (e.g., domains.lookup vs. domains.whois vs. domains.rdap) with no ambiguity.
All tools follow a consistent group.tool_name pattern using snake_case. The naming is predictable and uniformly applied across all groups.
78 tools is high, but the server aggregates multiple distinct API domains (11 groups). Each group has a reasonable number of tools, typically under 10, with TikTok having 17. The count reflects breadth, not bloat.
Each domain's tool set covers the primary expected operations (e.g., search, details, reviews, metrics, user info). There are no obvious gaps for read-only analytical use; features like posting are likely out of scope.