get_elevationElevation in metres above mean sea level for a single lat/lon.
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | Latitude | |
| longitude | Yes | Longitude |
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | Latitude of the queried location | |
| longitude | Yes | Longitude of the queried location | |
| elevation_m | Yes | Elevation in metres above mean sea level |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "latitude": 40.7128,
+ "longitude": -74.006
+ },
+ {
+ "latitude": 51.5074,
+ "longitude": -0.1278
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "elevation_m": {
+ "description": "Elevation in metres above mean sea level",
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "latitude": {
+ "description": "Latitude of the queried location",
+ "type": "number"
+ },
+ "longitude": {
+ "description": "Longitude of the queried location",
+ "type": "number"
+ }
+ },
+ "required": [
+ "latitude",
+ "longitude",
+ "elevation_m"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds value by specifying the output unit (metres above mean sea level) and confirming it handles a single point. This goes beyond annotations.
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?
Single sentence, no wasted words. Front-loaded with key information. Perfectly concise for the simplicity of the tool.
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?
Given the tool's simplicity, full annotations, and output schema availability, the description is complete. It succinctly covers purpose, input scope, and output format with no gaps.
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 coverage is 100% with descriptions for latitude and longitude. The description does not add parameter-specific details beyond the schema. Given high coverage, baseline 3 is appropriate.
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?
Clearly states the tool returns elevation in metres above mean sea level for a single lat/lon. The verb 'get' and resource 'elevation' are explicit, and the phrase 'single lat/lon' distinguishes from the sibling tool 'get_elevations' which likely handles multiple points.
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 implies usage for a single latitude/longitude pair, but does not explicitly state when to prefer this over alternatives (e.g., get_elevations). No when-not-to-use or alternative guidance is provided. The differentiation is weak.
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.
The tool set covers many unrelated domains (elevation, finance, prediction markets, AI visibility, etc.) with multiple overlapping tools per domain (e.g., three 'ask_pipeworx' variants, several 'polymarket' tools). An agent would struggle to distinguish which tool to use for a given task.
Names follow no consistent pattern: some use snake_case with vague verbs (e.g., 'process', 'run'), others use descriptive but unrelated prefixes ('ai_', 'ask_pipeworx_', 'polymarket_'). There is no uniform verb_noun structure.
With 32 tools, the count is reasonable for a large server, but the vast majority are irrelevant to the server's stated purpose (elevation). This mismatch makes the count inappropriate.
The server name 'Open Elevation' implies a focus on elevation data, yet only 2 of 32 tools (get_elevation, get_elevations) are related. There are severe gaps: no area elevation, no geocoding, no terrain analysis. The tool surface is largely off-topic.