maps-mcp

Server Quality Checklist

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Latest release: v0.1.1
Disambiguation5/5
Each tool targets a distinct operation: geocoding forward/reverse, place search by text or type, place details by ID, routing, and timezone lookup. Even place_search and place_search_nearby are clearly separated by free-text vs. type/radius queries with distinct parameters, leaving no ambiguity.
Naming Consistency4/5
All names are lowercase with underscores and readable, but the pattern is mixed: geocode and reverse_geocode are verb-first, while place_search, place_details, travel_time, and time_zone are noun-first. This is a minor inconsistency that does not harm clarity.
Tool Count5/5
Seven tools cover the core map-related operations without redundancy or bloat. The scope is well-balanced, fitting a focused maps MCP server that handles geocoding, place discovery, routing, and timezone data.
Completeness5/5
The surface provides a complete life-cycle for map queries: geocoding both directions, place discovery via text and type, detailed place information, travel time/directions, and timezone data. No major gaps for the stated purpose, and all operations are read-only which suits the domain.
Average 4.2/5 across 7 of 7 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- Last stable release on August 5, 2026
- 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds minor behavioral detail ('nearest', 'address(es)') but does not disclose behavior for invalid coordinates, no-match cases, or output format. There is no mention of side effects or prerequisites.
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?
The description is a single, concise sentence with no wasted words. It front-loads the core functionality directly and is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks essential context: no usage guidance, no parameter details, and no edge-case behavior. It is minimally viable but leaves significant gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only says 'coordinates', offering no additional meaning for 'latitude' and 'longitude'. It does not compensate for the lack of schema descriptions, leaving parameter semantics entirely to the self-explanatory parameter names.
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 uses a specific verb 'Resolve' with a clear resource 'coordinates' to 'nearest street address(es)'. This clearly distinguishes it from the sibling 'geocode' tool, which presumably converts addresses to coordinates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives like 'geocode'. It does not mention exclusions or scenarios. Usage is only implied by the tool's name and purpose.
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 are provided, so the description carries the full burden of behavioral disclosure. It does disclose the region bias behavior and the environment variable default, which is valuable. However, it does not explicitly state that this is a read-only operation, nor does it mention authentication, rate limits, or failure modes.
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?
The description is two sentences with no wasted words. The first sentence front-loads the core purpose and outputs; the second efficiently explains the region parameter nuance. It is compact and well-structured.
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 low-complexity, two-parameter tool with an output schema present, the description covers the operation, the output components, and the region behavior. It lacks only explicit guidance on when to choose this tool over siblings like reverse_geocode, but this is a minor omission given the clarity of the core purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description fully compensates by clarifying that 'address' accepts free-form text or place names and explaining 'region' as a ccTLD bias with a default from MAPS_REGION and a 'results elsewhere still resolve' caveat. This adds significant meaning beyond the bare parameter names in 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?
The description uses the specific verb 'Resolve' and identifies the resource (free-form address or place name) and the outputs (coordinates, canonical formatted address, place_id). This clearly distinguishes it from the reverse_geocode sibling and other related tools.
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 clearly indicates when to use the tool: when you have an address or place name and need coordinates and a canonical address. It also explains the region bias behavior, but it does not explicitly mention alternative tools (e.g., place_search) or exclusion scenarios, so it stops short of full alternative guidance.
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?
With no annotations, the description carries the full burden. It discloses what the tool returns but does not explicitly state whether the operation is side-effect-free, require auth, or mention rate limits. The read-only nature is implied by 'Full detail' but not explicitly confirmed.
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?
A single, front-loaded sentence that names the action, the key parameter, and the returned fields. Every word earns its place with no unnecessary elaboration.
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?
Given the tool's low complexity, one parameter, and the presence of an output schema, the description is complete. It covers the prerequisite (where place_id comes from), the lookup target, and the concrete detail fields returned, leaving no critical invocation gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, place_id, is given meaningful context by noting it comes from place_search or geocode. Since schema description coverage is 0%, this added provenance is valuable, though it could further clarify the ID format.
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 specifies the exact action ('Full detail for one place') and the resource ('by place_id'), and distinguishes itself from siblings like place_search and geocode by enumerating the detail fields (hours, phone, rating, etc.). This is a clear verb+resource with sibling differentiation.
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?
It clearly states that place_id comes from place_search or geocode, signaling the correct upstream tools and when to use this lookup. It does not explicitly name alternatives or exclusions, but the sibling set makes the intended usage obvious.
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 provided, the description carries the full burden. It adds valuable behavioral detail about how the timestamp parameter evaluates DST at a specific moment and that 0 means 'now', which is not visible in the schema. However, it does not disclose error behavior or side effects (unlikely for a read-only tool).
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?
The description is two sentences, front-loaded with the primary purpose and immediately followed by the timestamp nuance. Every word earns its place with no redundancy.
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?
The tool is simple and an output schema exists, so return values need not be described. The description covers the essential behavior, including the optional timestamp explanation, making it complete for an agent to use 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 0%, so the description must compensate. It explains the timestamp parameter's meaning well (unix epoch seconds, DST evaluation, 0=now), but latitude and longitude are not described beyond their parameter names, which are self-evident. Partial compensation yields a mid-range score.
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 clearly states the tool returns IANA time zone and UTC offset (including DST) for given coordinates, which is a specific and distinct capability compared to siblings like geocode or travel_time. The resource and action are unambiguous.
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 use case: obtain time zone data for a coordinate. It gives clear context but does not explicitly mention when not to use it or alternative tools. Thus it is clear but lacks explicit exclusions.
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 the full burden and does a good job: it discloses return fields, explains the radius_meters default of 5 km (even though schema default is 0, implying 0 means use default), and describes open_now filtering behavior. It does not mention pagination, rate limits, or error behavior, but the core behavior is well covered.
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?
The description is two sentences, well-structured with examples, front-loaded with the main purpose, and every clause adds value. The line breaks and formatting aid readability without unnecessary verbosity.
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?
Given the output schema exists and the description already lists return fields, it does not need to reiterate them. It covers the main parameter behaviors, defaults, and usage patterns. The only gap is max_results semantics, but that is a minor omission for a tool with six parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 explains query semantics, latitude/longitude use, radius_meters default in meaningful terms, and open_now. It omits max_results, but the other parameters are given practical context beyond the schema's raw defaults.
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 clearly states the tool finds businesses/points of interest via free-text query with examples, and distinguishes it from siblings like geocode and place_details by emphasizing free-text search. It also lists specific return fields, making the resource and scope unambiguous.
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?
Provides clear context on using latitude/longitude to bias results or putting the suburb in the query, along with radius_meters default and open_now usage. However, it does not explicitly contrast with place_search_nearby or state when not to use this tool, so it lacks explicit exclusion guidance.
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 provided, the description carries the behavioral burden. It discloses traffic-aware delay vs baseline, transit leg details, extra computation for tolls, and API restrictions (arrival_time only for transit). It does not mention auth, rate limits, or error handling, but for a routing API this is substantial transparency.
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?
The description is organized with clear line breaks separating the core purpose from parameter details. Every sentence adds value, using concrete examples (e.g., RFC3339 format) without excessive verbosity. It front-loads the purpose and then details each parameter efficiently.
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?
Given the tool has 7 parameters and an output schema exists, the description covers the essential usage context, parameter semantics for most parameters, and special behavioral traits (traffic, transit legs, toll computation). The missing avoid_tolls is minor, and overall the description is complete enough for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 explains origin/destination formats, mode values and defaults, RFC3339 time formats, the departure/arrival semantics, and include_tolls behavior. However, it omits the avoid_tolls parameter entirely, leaving that one parameter undocumented despite the schema having no description either.
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 clearly states the tool computes route duration and distance between two points, with specific behavioral modes (traffic-aware driving, step-by-step transit). It positions itself as 'THE tool for when do I need to leave?', distinguishing itself from sibling tools like geocode or place_search which handle locations, not routing.
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?
Provides clear context on when to use it (routing, ETAs) and mode-specific constraints (e.g., arrival_time is transit-only). It does not explicitly name alternatives or state when not to use it, but the context is strong enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals multiple non-obvious behaviors: empty 'included_types' returns prominent places of any type, 'rank_by_distance=True' changes ranking from prominence to nearest-first, and it specifies default/max values for radius_meters and max_results. This goes beyond parameter listing and gives meaningful operational insight.
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?
The description is front-loaded with a single-sentence purpose and sibling differentiation. The parameter list is compact, well-structured, and every sentence adds value. It is appropriately sized for a tool with 6 parameters and no schema descriptions, and it avoids redundant filler.
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?
The tool has 6 parameters, no annotations, but an output schema. The description covers all parameter semantics, states defaults and edge cases, and provides a clear alternative to a sibling tool. Since an output schema exists, return values need no explanation. The description is complete for its complexity and available structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 entirely. It explains every parameter: latitude/longitude as center, included_types with comma-separated syntax and examples, default and max for radius_meters, default and max for max_results, and the behavior of rank_by_distance. This is a textbook example of compensating for a schema with no descriptions.
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 uses a specific verb ('Find places around a point by TYPE') and clearly identifies the resource and scope. It explicitly distinguishes itself from its sibling 'place_search' by calling itself 'the typed complement to place_search's free-text queries.' This fully satisfies the requirement of a specific verb+resource with sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly names the alternative tool ('place_search') and states the when-to-use distinction: use this tool for typed 'what's near me' queries, and place_search for free-text queries. This provides clear guidance on when to use the tool versus an alternative, exceeding the baseline.
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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