Full one-call QA report of an ArcGIS FeatureServer layer: health (latency, record count, capabilities) + field schema + coded domains + summary counts.
One call replaces separate health/fields/domains lookups. Returns JSON:
{name, geometry_type, health, fields, domains, summary}.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No | ||
| service_url | 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 carries full burden. It describes the return JSON shape and lists included components (health, fields, domains, summary), but does not disclose potential issues like authentication requirements (token is optional but unexplained), error cases, or the exact structure of the 'health' object. It is adequate but lacks depth.
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 extremely concise: two short sentences that front-load the purpose and follow with the key differentiator and output format. Every sentence adds value without redundancy.
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 complexity (comprehensive audit) and the presence of an output schema, the description adequately covers what the tool does and returns. However, the lack of parameter documentation (0% coverage) and missing guidance on authentication or error states leaves significant gaps for an agent to invoke the tool correctly.
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%, and the description adds no information about the two parameters (service_url, token) beyond what the schema provides. It does not explain what service_url should point to or how token is used, making it nearly impossible for an agent to correctly construct the invocation without external knowledge.
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 produces a 'Full one-call QA report' covering health, field schema, coded domains, and summary counts. It specifies the output format and explicitly distinguishes itself from sibling tools like check_service_health, check_field_types, and extract_domains by noting that this tool replaces separate lookups.
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 'One call replaces separate health/fields/domains lookups,' which guides agents to use this tool when a comprehensive report is needed instead of individual checks. However, it does not explicitly state when not to use it (e.g., if only a single metric is needed) or provide direct comparisons to sibling 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.