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epwforge-mcp

by io.github.guzz-labs

explore_design_conditions

Interactive single-site design-conditions explorer. Returns full ASHRAE design conditions + diurnal chart for the requested scenario. In MCP Apps-capable hosts (Claude Desktop, ChatGPT, VS Code, Goose), the response renders as a widget with sliders for SSP / year / percentile / UHI — dragging a slider re-calls this tool live. Use when a user wants to interactively tune a single site. For multi-site comparison, use analyze_weather(urls=[...]) instead. Defaults to present-day TMY (no morph) — pass ssp+year for future scenarios. P75 default percentile is design-realistic; P50 underestimates the tail. No auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude, decimal degrees
lonYesLongitude, decimal degrees
sspNoCMIP6 emission scenario. Omit for present-day TMY. ssp370 is the recommended high-end; ssp585 (SSP5-8.5) is an opt-in extreme stress-test pathway for worst-case analysis.
uhiNoUrban Heat Island preset
yearNoFuture horizon. Pair with ssp.
percentileNoWarming percentile. P75 design-realistic; P50 median.
allow_custom_locationNoRequired when no OneBuilding station within 50 km

TDQS

A4.6/5.0
Behavior4/5

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 interactive widget behavior in capable hosts, default behavior, and auth requirements. However, it does not explicitly state that the tool is read-only or discuss potential side effects, though the context implies mutation is unlikely.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose and is well-structured with separate points. While it is somewhat long, every sentence adds essential information (purpose, interactive behavior, usage guidelines, parameter defaults, alternatives). It could be slightly more concise but remains effective.

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, no output schema, and no annotations, the description provides complete context: purpose, interactive rendering, when to use, when not to use, defaults, parameter advice, and auth. It addresses the complexity adequately without leaving critical gaps.

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 100%, so baseline is 3. The description adds valuable context beyond the schema, such as defaults ('present-day TMY'), recommendations ('ssp370 is recommended high-end'), and behavior ('P75 default is design-realistic'). This extra guidance enriches understanding for the AI agent.

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 it is an 'Interactive single-site design-conditions explorer' that returns ASHRAE design conditions and a diurnal chart. It distinguishes itself from the sibling tool 'analyze_weather' by specifying that the sibling is for multi-site comparison.

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?

Explicitly states when to use ('when a user wants to interactively tune a single site'), when not to use ('for multi-site comparison, use analyze_weather'), and provides defaults ('defaults to present-day TMY'), parameter advice ('P75 default percentile is design-realistic; P50 underestimates the tail'), and prerequisites ('No auth required').

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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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