Skip to main content
Glama

epwforge-mcp

by io.github.guzz-labs

find_station

Search the GuzzStations catalog (17,000+ weather stations worldwide, self-hosted mirror of OneBuilding TMYx). Returns matching stations with EPW URLs ready to pass to analyze_weather or chart_weather. Optionally enriches with AMY extreme years (hottest / coldest / most-humid on record) and CMIP6 climate deltas. No auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude — when set, results sorted by proximity
lonNo
sspNoSSP scenario (only used with include_climate_deltas). ssp370 is the recommended high-end; ssp585 (SSP5-8.5) is an opt-in extreme stress-test pathway for worst-case analysis.
yearNoFuture horizon (only used with include_climate_deltas)
queryNoSearch by city / state (case-insensitive partial match)
countryNoISO 3-letter country code filter, e.g. 'USA', 'GBR'
percentileNoWarming percentile (only used with include_climate_deltas, default 50)
max_resultsNoMax stations (default: 10)
site_elevation_mNoSite elevation in metres. Strongly recommended when lat/lon are set: elevation difference predicts whether a station is representative about 3x better than distance does, and supplying it turns the recommendation from a distance guess into a measured call.
include_amy_extremesNoWhen true and lat+lon are set, also returns the hottest / coldest / most-humid years on record (per ERA5, 1950–present). Useful for picking AMY basis years.
include_climate_deltasNoWhen true with lat+lon+ssp+year, also returns the monthly CMIP6 delta-T per month and per variable. Lets agents reason about specific shifts before generating files.

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the transparency burden. It explicitly discloses 'No auth required,' identifies the data source ('self-hosted mirror of OneBuilding TMYx'), and describes optional enrichment behavior (AMY extremes, CMIP6 deltas). This exceeds basic expectations, though it omits pagination/error details.

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?

Three sentences with no filler. The main purpose is front-loaded, and each sentence adds meaningful context: what the catalog is, what is returned, and optional features. No redundant information.

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 tool has 11 parameters and no output schema, the description provides a clear overview of the return value (EPW URLs) and optional enrichment flags, while the rich schema descriptions cover parameter specifics. This is sufficiently complete for a search tool, though it could mention default behavior (e.g., max_results default, sorting when no lat/lon) if not already in schema.

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 91%, so the baseline is 3. The description provides a high-level overview of optional enrichment but does not add syntax or constraints beyond what the schema already describes for individual parameters. It adds little value over 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 clearly states the tool's verb ('Search'), resource ('GuzzStations catalog'), and scope (17,000+ weather stations worldwide). It also distinguishes itself from sibling tools by noting that returned EPW URLs are ready to pass to analyze_weather or chart_weather.

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 when to use this tool: to find stations before weather analysis or charting. 'Ready to pass to analyze_weather or chart_weather' gives clear downstream workflow context, though it does not explicitly list when-not-to-use or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All epwforge-mcp toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.2/5.0
Disambiguation4/5

Each tool has a distinct primary function: analysis, charting, interactive exploration, station search, file generation, and bundle preview. Some overlap exists between 'analyze_weather' and 'explore_design_conditions', but descriptions clarify single-site vs. batch and interactive vs. static usage.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (e.g., analyze_weather, chart_weather, find_station). Verbs are action-oriented and nouns clearly indicate the target resource.

Tool Count5/5

With 6 tools, the server is well-scoped for EPW weather data tasks. Each tool serves a necessary function without superfluous additions, fitting the ideal 3-15 range.

Completeness4/5

Core workflows (find station, analyze stats, visualize, generate custom files, purchase) are covered. A minor gap is the lack of a direct raw file download tool, but the EPW URLs from 'find_station' effectively serve that purpose.

Resources