layer_infoGet an ArcGIS Feature/Map Service layer's schema by url: fields (name + type), geometry type, total record count, and capabilities.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Feature/Map Service layer url, e.g. ".../FeatureServer/0". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "url": "https://services.arcgisonline.com/arcgis/rest/services/City_of_Peterborough/FeatureServer/0"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld, and non-destructive. The description adds behavioral value by specifying what information is retrieved (fields, geometry type, count, capabilities), going beyond the annotations and adding context about the tool's output.
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 that immediately states the action and enumerates the returned items. Every word contributes information; no fluff or repetition.
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 (one parameter, no output schema), the description is sufficiently complete. It lists the key returned elements and the required input, making the tool's behavior clear. Annotations cover safety and idempotency, so no additional context is needed.
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?
The input schema already documents the single 'url' parameter with 100% coverage, including an example. The description only says 'by url', which adds no new semantic detail beyond the schema. Baseline 3 is appropriate since schema does the heavy lifting.
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 uses a specific verb ('Get') and identifies the resource (ArcGIS Feature/Map Service layer's schema) along with concrete outputs (fields, geometry type, record count, capabilities). It clearly distinguishes from siblings like query_layer by focusing on schema rather than data.
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 clearly implies when to use the tool: when you need schema information for a layer. It does not explicitly mention when not to use it or name alternatives, but the context is specific enough that an agent can select it appropriately.
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.
Multiple tool families overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions to the same underlying 5,767 tools with significant functional overlap. Polymarket tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk) also have blurred boundaries around edge detection and fill risk. The ArcGIS tools (search_datasets, layer_info, query_layer) are distinct, but the non-ArcGIS tools dominate and create confusion.
The naming conventions are inconsistent across the set. Some tools use verb_noun (ask_pipeworx, query_layer, search_datasets, list_subscriptions), some use bare verbs (forget, recall, subscribe, unsubscribe), and others use descriptive multi-word names (polymarket_fill_risk, scan_competitor_ai_presence, generate_llms_txt). The ask_pipeworx family and polymarket_* family are internally consistent, but the overall set mixes styles without a clear pattern.
34 tools is heavy for a server that appears to be an ArcGIS data server but includes a massive Pipeworx data-research and prediction-market subsystem. The ArcGIS portion only has 3 tools (search_datasets, layer_info, query_layer), while the rest form a separate general-purpose research/betting toolkit. The count feels bloated and unfocused relative to the server's stated name.
The ArcGIS surface is incomplete: search_datasets, layer_info, and query_layer offer no update/create/delete or metadata exploration beyond one layer at a time. The Pipeworx portion is broad but lacks clear lifecycle coverage for subscriptions (create/cancel works, but no update), and the memory tools (remember/recall/forget) are peripheral. The set feels like an accidental aggregation of unrelated domains rather than a complete surface for one purpose.