gisgp

query_features

Fetch actual feature records (attributes + geometry) from a FeatureServer layer.

Free preview capped at 50 records (WHERE filter + chosen fields). Returns JSON:
{returned, total, truncated, geojson, note}. Full unlimited export is a paid operation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "service_url": "<service_url>"
    },
    "name": "query_features"
  }
}

Input Schema

Name	Required	Default
`limit`	No
`token`	No
`where`	No	1=1
`out_fields`	No	*
`service_url`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 11, 2026

TDQS

A4.2/5.0

Behavior4/5

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

No annotations provided, so the description carries the full burden. It discloses that the operation returns a JSON with specific fields (returned, total, truncated, geojson, note) and that it is a fetch operation (not destructive). It also mentions the preview cap and paid export.

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 three sentences: first states purpose, second clarifies the free preview cap, third describes the return format. It is concise, front-loaded, and contains no superfluous information.

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's complexity (5 parameters, no enums, output schema exists), the description covers the main aspects: purpose, limitations, and return format. It could explain the token parameter or provide more parameter detail, but it is sufficiently complete for a data fetching tool.

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

Parameters3/5

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 explains that where and out_fields relate to filtering and field selection, and mentions the limit implicitly via the 50-record cap. However, service_url and token are not explained, providing only partial compensation.

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 fetches feature records (attributes + geometry) from a FeatureServer layer. It distinguishes itself from sibling tools like count_features or query_statistics by focusing on actual records.

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

Usage Guidelines4/5

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

The description mentions the free preview cap at 50 records and that full export is a paid operation, guiding the agent on when to use this tool (previews) vs. alternative paid options. However, it does not explicitly compare to sibling tools.

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

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