Google Maps MCP Server
Server Quality Checklist
Latest release: v0.1.4
- Disambiguation5/5
Each tool has a distinct purpose: geocode and reverse_geocode handle coordinate conversion, search_places and search_nearby cover two search modes, get_directions provides routing, and get_place_details retrieves detailed info. No two tools overlap in functionality.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_directions, search_nearby, reverse_geocode), making them predictable and easy to understand.
Tool Count5/5With 6 tools, the server is well-scoped for a maps MCP, covering core geocoding, directions, and place search without being overly numerous or sparse.
Completeness4/5The tool set covers essential geocoding, routing, and place search features. Minor gaps exist (e.g., no distance matrix or batch geocoding), but core map interactions are well supported.
Average 4.5/5 across 6 of 6 tools scored. Lowest: 3.9/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry behavioral info. It specifies return value (dictionary with formatted address and details), but omits error handling, input validation, or performance traits. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise and well-structured: short description block followed by Args, Returns, and Example sections. No redundant sentences; every line provides useful information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description appropriately explains the return value (dictionary with formatted address and location details). Could specify more detail about address components, but adequate for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so description must compensate. It adds explanation for latitude and longitude with example values (42.4531, 18.5375), clarifying usage beyond the raw schema. Good value add.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (convert GPS coordinates) and the result (human-readable address). It distinguishes from siblings like 'geocode' (likely address to coordinates) but does not explicitly differentiate from others.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Directly tells when to use: 'Use this when you have coordinates and need to know the address.' It does not explicitly state when not to use or mention alternatives, but the guidance is clear and practical.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes what is returned (reviews, amenities, etc.) but does not disclose any behavioral traits such as read-only nature, required permissions, rate limits, or error conditions. The description is not misleading but incomplete for a no-annotation scenario.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with a clear purpose statement followed by usage hint and a detailed Args/Returns breakdown. Every sentence adds value; no fluff. Front-loaded with the main action, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description thoroughly enumerates return fields (basic info, top reviews, amenities, opening hours). Parameter coverage is complete with example. The tool is simple (1 param), and the description leaves no significant gaps for an agent to correctly invoke and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage (no parameter description for place_id), but the description provides the meaning: 'Google Place ID' with a concrete example. This fully compensates for the schema gap, adding critical context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states it gets detailed information about a place by Google Place ID. Clearly differentiates from sibling 'search_places' by specifying 'after finding it with search_places' and lists specific additional info (reviews, amenities, editorial summaries). Verb+resource+scope is precise and distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to get more details about a place after finding it with search_places', establishing a clear usage sequence. Does not explicitly mention when not to use or alternative tools like geocode/reverse_geocode, but the context is sufficient for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description details the return format (dictionary with distance, duration, steps, traffic duration, warnings) and mentions the API requirement. It does not cover rate limits or errors but is fairly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured with Args, Returns, and Example sections. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no output schema, and no annotations, the description covers inputs, outputs, and an example. It does not mention error handling or limitations, but is adequate for this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains each parameter: origin/destination can be address or coordinates, mode has default and options. This provides full semantic meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Get directions and route between two locations' and mentions step-by-step directions, which distinguishes it from sibling tools like geocode or search_places.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use (get directions), includes a note about enabling the Directions API, and provides an example. It lacks explicit alternatives or when-not-to-use guidance, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the return data comprehensively (contact, ratings, hours) but lacks disclosure of rate limits or usage costs. No annotations exist, so description carries the burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with Args and Returns sections, but slightly verbose with repetitive opening sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given only 2 parameters and no output schema, the description fully explains inputs and outputs, making it complete for agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description adds significant meaning: explains query format with examples and clarifies max_results range and default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'search' and resource 'Google Maps places' with a text query. Distinguishes from sibling tools like search_nearby (location-based) by emphasizing textual queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for when to use (text-based searches) but does not explicitly mention when not to use or alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes return format (dictionary with center point, radius, and place list) and parameter constraints (radius max 50000, max_results limit). No annotations exist, so disclosure is adequate for a read-only search; no side effects or auth requirements mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: brief intro sentence, usage guidance, labeled Args list, Returns, and Example. Every element earns its place; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers purpose, usage, all parameters (with details), return format, and an example. No obvious gaps for this tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by detailing each parameter: units for radius, example values for latitude/longitude, optional place_type with examples, and default values. Adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states 'Search for places near specific coordinates' and gives a concrete example ('find restaurants near me'). It differentiates from siblings like 'search_places' (text-based) and 'geocode' (address to coordinates) by emphasizing GPS coordinate input.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly advises when to use: 'Use this when you have GPS coordinates and want to find places nearby.' Provides common query type. Lacks explicit exclusions or alternatives, but context implies it's for coordinate-based searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the input format, return structure (formatted_address, latitude, longitude, place_id), and provides an example. It does not mention error handling, rate limits, or accuracy, but for a simple geocoding tool the information is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the purpose, followed by usage guidance, then structured Args/Returns/Example. Every sentence adds value, with no redundancy. It is concise yet complete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and no output schema, the description fully covers input semantics, return structure, and example usage. It is complete for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains the address parameter can be 'Address, place name, landmark, or location description' and gives concrete examples like 'Ferry Building San Francisco'. This adds significant meaning beyond the schema's type string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Convert an address or place description to GPS coordinates' which is a specific verb+resource. It clearly distinguishes from sibling tools like get_directions, reverse_geocode, and search_nearby that have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this when a user describes their location... and you need coordinates for search_nearby.' This provides clear context for when to use this tool over alternatives, directly naming a sibling tool as a downstream use case.
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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