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Glama

Opensensemap

by io.github.pipeworx-io

Opensensemap Box

opensensemap_box
Read-onlyIdempotent

Get one openSenseMap citizen science sensor station (senseBox) by its box id — full sensor readout with latest value, unit, and measurement time per sensor (temperature, humidity, PM2.5/PM10 air quality, pressure, noise...), plus location, exposure (outdoor/indoor/mobile) and station metadata. Box ids come from opensensemap_nearby. Community-operated uncalibrated sensors. Example: opensensemap_box({ box_id: "65e8d93acbf5700007f920ca" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
box_idYes24-char openSenseMap box id, e.g. "65e8d93acbf5700007f920ca"

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: +[
+  {
+    "box_id": "65e8d93acbf5700007f920ca"
+  }
+]
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare the read-only and idempotent nature. The description adds the important caveat that sensors are community-operated and uncalibrated, which is behavioral context about data reliability not covered by annotations.

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 and an example; all parts are meaningful. The purpose is front-loaded, the source of ids is briefly mentioned, and the caveat adds value without verbosity.

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?

With one parameter, read-only annotations, and no output schema, the description sufficiently covers what data is returned (sensor readouts, location, exposure, metadata) and provides usage context. It is complete enough for correct selection and invocation.

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 coverage is 100%, providing the parameter name and type. The description enhances this by specifying that box ids come from opensensemap_nearby and including a concrete example, making the parameter's origin and format clearer.

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 verb 'get' and the resource: a single openSenseMap station by box id. It distinguishes from sibling tools by highlighting the box id lookup and the specific fields returned.

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 that box ids come from opensensemap_nearby, guiding the agent on when to use this tool versus the sibling nearby tool. The description also makes clear that this returns detailed single-station data, implying it is not for area averages.

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

All Opensensemap toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior today, while discover_tools and suggest_questions overlap as discovery/onboarding entry points. The Polymarket tools also blur together across arbitrage, edges, edge tracking, and fill risk, making tool selection prone to mistakes despite long descriptions.

Naming Consistency3/5

Names are consistently lowercase snake_case and readable, but they mix conventions: some are clear verb_noun actions like validate_claim and compare_entities, while others are noun-led like recent_alerts and entity_profile, or domain-prefixed like polymarket_edges and opensensemap_nearby. There is no single predictable naming pattern across the set.

Tool Count2/5

At 34 tools, this exceeds the 25+ threshold for a heavy tool set, and the tools span several unrelated domains: OpenSenseMap sensors, Pipeworx data access, Polymarket research, memory, subscriptions, and AI visibility. A server named Opensensemap hosting this much unrelated functionality feels poorly scoped.

Completeness3/5

The OpenSenseMap portion covers nearby discovery, box lookup, and area averages, but lacks historical/time-series access and station lifecycle operations, which are notable gaps for a sensor data server. The broader Pipeworx surface has strong lookup, research, validation, and subscription coverage, so the main incompleteness is in the named domain.

Resources