A
licenseA
qualityB
maintenanceProvides climate data for 3,833 destinations including sunshine scores, temperatures, rainfall, and sea temperature, enabling users to find sunny destinations and compare climates via three tools.
3
MIT
Sunshine Atlas
Server Details
Where is it sunny? Monthly sunshine scores, temps, rain, UV and sea temp for 3,833 destinations.
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- Status
- Healthy
- Uptime
- 100.0% over 47 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
A4.4/5.0
Scored across 3 tools
Disambiguation5/5
Each tool has a distinct purpose: get_destination_climate provides a single destination's full year, find_sunny_destinations answers ranked discovery queries by month, and compare_destinations directly contrasts 2–5 selected places. There is no meaningful overlap or ambiguity between them.
Naming Consistency5/5
All tool names follow a clear snake_case verb_noun pattern: compare_destinations, find_sunny_destinations, get_destination_climate. The verb choice accurately reflects each operation and the naming is perfectly consistent.
Tool Count5/5
Three tools is well-scoped for a focused sunshine/climate atlas: one for search/discovery, one for single-location detail, and one for side-by-side comparison. Each tool is necessary and the set does not feel padded or incomplete.
Completeness5/5
The tool surface covers the core user journeys: finding sunny destinations by month, examining a destination's full climate profile, and comparing specific options. The domain is climate normals for trip planning, and these three operations form a complete workflow without obvious dead ends.
Available Tools
3 toolscompare_destinationsCompare destinationsAInspect
Side-by-side sunshine/climate comparison of 2–5 destinations — overall or for one month ("Algarve or Crete in October?"). Returns each place's Sunshine Score, temperatures, rain, midday UV index and sea temperature, plus a one-line verdict of which is sunnier.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| month | No | Optional month to compare in; omit for year-round comparison | |
| destinations | Yes | 2–5 destinations (city, "city, country", or IATA code) |
TDQS
A4/5.0
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. It discloses the output fields (Sunshine Score, temperatures, rain, UV index, sea temperature, and a verdict), which is helpful. However, it does not mention any limitations, potential errors (e.g., invalid destinations), or explicitly state that it is a read-only operation. The description is not misleading, but it lacks deeper behavioral context beyond the output summary.
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 concise and efficiently structured: two sentences. It front-loads the core purpose ('Side-by-side sunshine/climate comparison'), then elaborates on scope and output. Every sentence earns its place with no fluff or repetition of schema details.
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?
There is no output schema, but the description explicitly enumerates the return values (Sunshine Score, temperatures, rain, UV, sea temperature, verdict), which mitigates that gap. It also covers the optional month parameter and the range of destinations. It is not fully complete—it doesn't describe error behavior or data sources—but for a comparison tool with this simplicity, the key aspects are covered.
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 100%, so the parameters are already fully documented: destinations (array, min 2, max 5) and month (optional, omit for year-round). The description adds an example phrase but does not introduce new semantic meaning beyond what the schema provides. Thus, the baseline score of 3 is appropriate.
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 performs a side-by-side comparison of 2–5 destinations, focusing on sunshine/climate metrics. It distinguishes itself from sibling tools by emphasizing comparison (find_sunny_destinations searches for sunny places, get_destination_climate likely focuses on a single destination). The verb 'compare' and resource 'destinations' are specific and 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 offers clear context on when to use the tool: for comparing multiple destinations, either year-round or for a specific month, with an illustrative example ('Algarve or Crete in October?'). It does not explicitly name alternative tools or exclude them, but the comparative scope (2–5 destinations) inherently distinguishes it from siblings. It could benefit from an explicit 'use this when you need to compare multiple places' recommendation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_sunny_destinationsFind sunny destinationsAInspect
Ranked answer to "where is it sunny (and warm) in ?" — destinations sorted by that month's 0–100 Sunshine Score (long-term climate normals). Filter by continent or country, minimum daytime temperature, population, swimmable sea (≥21°C), or a ceiling on the midday UV index. Every result carries that month's temperatures, rain, midday UV (WHO scale) and sea temperature, plus a citable destinationsmap.com URL.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many results (default 10, max 50) | |
| month | Yes | Month name ("November", "nov") or number 1–12 | |
| where | No | Optional continent ("Europe", "Asia", "North America", …) or country (name or ISO-2 code) to search within. "Europe" uses the traveler definition and includes the Canary Islands. | |
| max_midday_uv | No | Only places whose typical midday UV index that month is at or below this (WHO scale: ≤2 low, ≤5 moderate, ≤7 high). For sun-sensitive travellers — "sunny but not fierce". | |
| min_day_high_c | No | Only places at least this warm by day that month, °C | |
| min_population | No | Only places with at least this population (default 0 = include small islands and outposts) | |
| require_swimmable_sea | No | Only coastal places with sea ≥21°C that month |
TDQS
A4.3/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and does well: it states that results are ranked, sorted by climate normals, filterable, and that each result includes temperatures, rain, UV, sea temperature, and a URL. It does not explicitly state that the operation is read-only or mention potential data caveats, but it strongly implies a non-destructive lookup.
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 dense yet efficient: it front-loads the ranked-answer behavior in the first sentence, groups filter capabilities in the second, and specifies output contents in the third. Every sentence adds distinct information, with no filler or repetition.
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 no output schema, but the description explicitly enumerates what every result carries, including month-specific temperatures, rain, UV, sea temperature, and a citable URL. Combined with fully described parameters Jew and no required alternative routing, an agent has enough context to call it 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 100%, so the baseline is 3. The description summarizes the filter dimensions (continent/country, min temperature, population, swimmable sea, UV ceiling) but adds no meaning beyond what the schema property descriptions already offer. It does not compensate beyond that baseline.
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 names a specific verb ('find'), a concrete resource ('sunny destinations'), and the exact ranking logic (0–100 Sunshine Score for the requested month). It clearly distinguishes itself from siblings like compare_destinations and get_destination_climate by framing itself as a ranked list answer to a 'where is it sunny?' query.
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 gives clear context for the query type this tool answers and lists available filters, so an agent can tell when this tool is appropriate. It does not explicitly name alternatives or say when not to use it (e.g., when a direct climate comparison is needed), so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_destination_climateDestination climate & best time to visitAInspect
Full climate card for one destination: 0–100 Sunshine Score, day/night °C, rainfall, midday UV index (WHO scale) and sea temperature for all 12 months, plus its sunniest month ("best time to visit" for sunshine), annual sunshine hours and peak midday UV. Accepts a city name ("Faro"), "city, country" ("Nice, France") or IATA airport code ("FAO").
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| destination | Yes | City name, "city, country", or 3-letter IATA airport code |
TDQS
A4.2/5.0
Behavior3/5
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 thoroughly lists the output data fields and accepted input formats, but it does not address error behavior, data source, or any read-only implications. It is adequate but not exhaustive.
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 compact: two sentences with no filler. The first sentence front-loads the tool's core purpose and outputs, while the second covers input formats. Every sentence adds value.
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 there is no output schema, the description compensates by enumerating all returned metrics and the sunniest month, which is crucial for an agent. It also specifies input format variants. It is complete for the tool's apparent simplicity, though it leaves out edge-case handling, which is a minor 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 schema already describes the parameter with 100% coverage, but the description adds concrete examples ('Faro', 'Nice, France', 'FAO') and reiterates the three accepted formats, which helps clarify exactly how to format the destination value. This goes beyond the schema's baseline.
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 unambiguously states the tool provides a 'Full climate card for one destination' and enumerates the specific metrics (Sunshine Score, temperatures, rainfall, UV, sea temperature). It clearly distinguishes from siblings by emphasizing 'one destination' as opposed to comparison or discovery 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 implies usage for a single destination's climate details, effectively distinguishing it from sibling tools like compare_destinations and find_sunny_destinations. However, it does not explicitly mention when to prefer this tool over alternatives or provide explicit exclusions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- Changed
find_sunny_destinations1 field changed- added
Input schema / properties / max_midday_uvAdded value: +{ + "description": "Only places whose typical midday UV index that month is at or below this (WHO scale: ≤2 low, ≤5 moderate, ≤7 high). For sun-sensitive travellers — \"sunny but not fierce\".", + "type": "number" +}
3 tool updates
- First observed
compare_destinations - First observed
find_sunny_destinations - First observed
get_destination_climate
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