coordinates_convert"Convert WGS84 lat/lng to [other CRS]" / "reproject coordinates" / "EPSG:4326 → EPSG:[X]" / "Web Mercator coordinates" — Coordinate Reference System (CRS) reprojection. Use to convert standard lat/lng (EPSG:4326) into projected systems like Web Mercator (3857), UTM zones, state plane, etc.
| Name | Required | Description | Default |
|---|---|---|---|
| target_crs | Yes | ||
| coordinates | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "coordinates": [
+ [
+ 2.3522,
+ 48.8566
+ ],
+ [
+ -74.006,
+ 40.7128
+ ]
+ ],
+ "target_crs": 3857
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context about the type of conversions (e.g., to Web Mercator, UTM) but does not discuss behaviors like input validation or error handling. It does not contradict 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?
The description is a single sentence with parenthetical aliases, front-loading the main purpose. It is concise with no wasted words.
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?
With 2 simple parameters and no output schema, the description provides enough to understand the tool's purpose but lacks details on coordinate format and EPSG code conventions. The schema examples partially compensate, but completeness is average.
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 0%, and the description does not explain the parameters. It mentions lat/lng and target CRS but does not specify coordinate order (lng, lat) or that target_crs is an EPSG code. The schema examples provide some help, but the description adds little meaning beyond the schema.
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 converts WGS84 lat/lng to other CRS, uses multiple aliases like 'reproject coordinates' and 'EPSG:4326 → EPSG:[X]'. It distinguishes from sibling tools by focusing on CRS conversion, unlike geocoding or elevation tools.
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 explains when to use the tool (to convert standard lat/lng into projected systems) and gives specific examples like Web Mercator, UTM zones, state plane. It does not explicitly mention when not to use or provide alternatives, but the context is clear enough for typical use.
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.