arcpro-mcp

by qiobn

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Python

Local

List Feature Classes

list_feature_classes

Read-only

List feature classes in a workspace, filtering by name pattern or geometry type such as Point, Polyline, or Polygon.

Instructions

List feature classes in a workspace (folder, file geodatabase, or feature dataset). pattern filters by name; geometry_type filters by Point/Polyline/Polygon.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_feature_classes"
  }
}

Input Schema

Name	Required	Default
`workspace`	No
`pattern`	No	*
`geometry_type`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 14, 2026

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds value beyond the readOnlyHint annotation by specifying the types of workspaces supported (folder, file geodatabase, feature dataset) and the role of parameters. However, it does not mention potential performance implications for large workspaces or what the output format contains, though the output schema likely covers the latter.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two sentences. The first sentence states the main purpose and scope, the second explains parameter behavior. Every sentence adds value, and the key information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema, the description covers the input parameters and workspace domain sufficiently. It is complete for an agent to understand when and how to use the tool. A minor improvement could be explicitly stating that it is a read-only operation, but the annotation already indicates that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining each parameter: pattern filters by name, geometry_type filters by geometry type (Point/Polyline/Polygon). This provides clear, actionable semantics beyond the schema's default values and titles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists feature classes in a workspace, specifying the resource (feature classes) and the action (list). It explicitly mentions the domain (folder, file geodatabase, feature dataset) and distinguishes from siblings like add_vector_layer or list_layers by focusing on a specific listing operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for listing feature classes but does not explicitly guide when to use this tool versus alternatives such as list_layers or list_fields. With 24 sibling tools, including other listing tools, explicit usage conditions or exclusions would improve this dimension.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.