elevation"Elevation at [coords]" / "altitude at [point]" / "how high is [location]" / "height above sea level" — elevation in meters above sea level at a single point via MapTiler's SRTM/Maxar dataset.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | ||
| lon | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "lat": 40.015,
+ "lon": -105.2705
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint; the description adds the data source (SRTM/Maxar), which provides context on coverage but does not disclose limitations like missing data areas or potential inaccuracies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, using examples to convey purpose efficiently. However, it could be restructured to include parameter details without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity (2 params, no output schema), the description omits parameter descriptions and return structure. It only states the elevation value in meters, which is adequate for output but incomplete for input semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It fails to mention the required parameters lat and lon or provide any format/range guidance beyond the schema's property names and types, which is insufficient for a 2-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns elevation in meters above sea level at a single point, with examples of natural language queries. However, it does not use an explicit verb like 'get' or 'retrieve', and the distinction from the sibling 'elevation_polyline' is implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates single-point usage and contrasts with polyline by mentioning 'single point'. It implies the data source (MapTiler's SRTM/Maxar) but lacks explicit when-not or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have distinct purposes, but there is overlap, e.g., ask_pipeworx vs ask_pipeworx_grounded vs deep_research all for data lookup, and multiple Polymarket tools. Descriptions are detailed enough to distinguish, but the set is confusing.
Naming is highly inconsistent: snake_case (ai_visibility_check), verb_noun (resolve_entity), underscores (ask_pipeworx), and domain-specific prefixes (polymarket_). No consistent pattern across tools.
With 38 tools spanning geospatial, data lookup, prediction markets, memory, feedback, etc., the count is too high for a coherent server. Many tools are one-off and unrelated to the server's name (Maptiler).
The tool set covers many areas but lacks obvious gaps for each domain (e.g., MapTiler only has 4 tools). The overall surface is a collection of unrelated features, not a cohesive domain, so completeness is poor for any single purpose.