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Glama

Openweather

by io.github.pipeworx-io

Geocode

geocode
Read-onlyIdempotent

Resolve a place name (city, optionally with state/country) to geographic coordinates (latitude/longitude). Useful before calling air_quality, which needs lat/lon. Example: geocode({ query: "Paris", limit: 5 })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of matching locations to return (default 5).
queryYesPlace name to look up, e.g. "Paris", "Springfield,IL,US".
_apiKeyNoOptional — your own OpenWeatherMap API key for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-openweather-api-key",
+    "limit": 5,
+    "query": "Paris"
+  },
+  {
+    "_apiKey": "your-openweather-api-key",
+    "query": "Springfield,IL,US"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds that it resolves to lat/lon and provides an example call, which is helpful beyond annotations. No contradictions.

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 plus an inline example, front-loaded with the purpose, and contains no extraneous words. Every sentence earns its place.

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 no output schema, the description could mention the exact return format (e.g., lat/lon object), but it says 'geographic coordinates', which is sufficient. It is complete enough for a simple lookup tool with well-documented parameters.

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 coverage is 100%, so the baseline is 3. The description does not add significant meaning beyond the schema—it repeats the query parameter but with an example. No additional semantic detail.

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 resolves a place name to geographic coordinates, a specific verb+resource. It also distinguishes from siblings by noting its utility before calling air_quality, which requires lat/lon.

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 provides clear context: 'Useful before calling air_quality' and gives an example. However, it does not explicitly state when not to use or suggest alternatives, though the sibling list includes similar lookup tools like resolve_entity.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions. However, 'ask_pipeworx' and 'ask_pipeworx_grounded' are very similar, and 'polymarket_arbitrage' and 'polymarket_edges' overlap in scope, which could cause confusion for an agent.

Naming Consistency3/5

Tool names mostly use snake_case but mix verb-first (e.g., 'compare_entities', 'resolve_entity') and noun-first (e.g., 'air_quality', 'entity_profile') patterns. Some names are single words ('forecast', 'geocode'), showing overall inconsistency.

Tool Count3/5

With 30 tools, the server covers many domains (weather, company info, betting, memory, subscriptions). While each tool serves a purpose, the count is on the higher side and could be streamlined, but it's not excessive given the diverse functionality.

Completeness4/5

The tool set provides comprehensive coverage for its domains: weather (current, forecast, air quality), company research (profile, compare, recent changes, validation), betting (research, arbitrage, edges), memory (CRUD), and subscriptions (CRUD). Minor gaps include no tool for editing subscriptions or deleting weather data, but these are outside the intended scope.

Resources