Convert a GPS track file (GPX) directly to CSV (2026-09-03) — waypoints get LATITUDE/LONGITUDE columns, tracks/routes get a GEOMETRY_WKT column instead.
| Name | Required | Description | Default |
|---|---|---|---|
| gpx | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations supplied, the description carries the full burden of behavioral disclosure. It reveals that waypoints map to LATITUDE/LONGITUDE columns while tracks/routes use a GEOMETRY_WKT column, providing real detail beyond a generic conversion statement. It doesn't address input path vs content, but the conversion behavior is well explained.
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, front-loaded sentence with the core action followed by the distinguishing column behavior. The date '(2026-09-03)' adds minor noise but does not compromise overall conciseness.
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?
Complexity is low and an output schema exists, but the description leaves the input representation ambiguous (file path vs content) and does not clarify coordinate order or error behavior. For a tool with no annotations, this ambiguity is a real gap in call correctness.
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 identifies the sole parameter as a 'GPS track file (GPX)', giving it domain meaning beyond the bare name 'gpx' and type 'string'. However, it doesn't specify whether the string is a file path or raw file content, leaving a meaningful ambiguity for invocation.
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 states a specific verb ('Convert'), resource ('GPS track file (GPX)'), and target format ('CSV'). It further distinguishes output behavior for waypoints versus tracks/routes, making it clear against sibling conversion tools like gpx_to_geojson or geojson_to_csv.
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 use case is clear: direct GPX-to-CSV conversion. Although it doesn't explicitly name alternatives or exclusion criteria, the phrase 'directly to CSV' implies no intermediate step, and the sibling list contains only converters with different input/output formats, making the intended usage unambiguous.
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 assess_* composite tools (datacenter, ev_charging, renewable, telecom, due_diligence) share the same building blocks of grid proximity, land cover, and terrain, making their boundaries fuzzy. assess_property_hazard_x402 also duplicates assess_property_hazard with only a payment-method difference, and bundle_* tools intentionally overlap with the free primitives they replace.
There is a mix of verb_noun tools (query_features, geocode_address), noun-first geometry tools (centroids_geojson, envelope_geojson), and inconsistent _geojson suffix usage (buffer_geojson, fix_geometry, geometry_stats). The assess_* and bundle_* prefixes offer some grouping, but no single naming pattern is followed across the set.
With 85 tools, the surface is extreme for an MCP server and far exceeds the typical well-scoped 3-15 range. Many tools are convenience bundles or variants that could be consolidated, making the count a significant usability burden.
The toolkit covers a broad range of GIS tasks: format conversions, GeoJSON analysis, FeatureServer query/inspection, geocoding, site assessment, and sharing. Minor gaps exist (e.g., no Excel-to-GeoJSON, no FeatureServer update/delete), but most missing functionality can be worked around by chaining existing tools.