Buffer every feature by a distance in METRES (negative shrinks).
Geodesically accurate at any latitude (each feature is buffered in a local
equidistant projection). Returns JSON {ok, distance_m, geojson} where geojson
is a FeatureCollection of buffer polygons.
| Name | Required | Description | Default |
|---|---|---|---|
| geojson | Yes | ||
| distance_m | 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, the description takes full responsibility. It discloses the return format (JSON with ok, distance_m, geojson), explains the projection behavior (local equidistant for geodesic accuracy), and notes that negative distances shrink. This is fairly transparent, though it could mention performance implications.
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 only two sentences, both front-loaded with essential information. No wasted words, and the structure is logical: operation + parameter specification, then accuracy and return details.
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 has only 2 parameters and a clear return (output schema exists but not detailed), the description covers the main points. It could mention limitations like large inputs or geometry types, but overall it is sufficiently complete for a simple buffer operation.
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 add value. It explains the distance_m unit (METRES) and effect (negative shrinks). It also implies that geojson input should contain features. This adds meaning beyond the bare schema, though it could be more explicit about input format.
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 action ('Buffer every feature'), the resource (GeoJSON), and the key parameter (distance in meters). It distinguishes itself from sibling geometry tools like centroids_geojson or convex_hull_geojson by explicitly focusing on buffering.
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 mentions geodesic accuracy at any latitude, which hints at appropriate use cases, but does not explicitly state when not to use this tool or provide alternatives among the many sibling geometry tools.
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.