hk-spatial-mcp

arcgis_request

Call ArcGIS Online REST endpoints with your configured token to search items, fetch item data or metadata, query feature services, and submit geoprocessing jobs.

Instructions

Call any ArcGIS Online REST endpoint with the configured token.

Examples: path="search", params={"q": 'title:"my layer"', "num": 5} → find items path="content/items//data", params={} → item JSON path="content/items/", params={} → item metadata path="/0/query", params={"where":"1=1","outFields":"*","f":"json","returnCountOnly":"true"} → count analysis: run a GP task under //submitJob (then /jobs/)

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": {
      "path": "<path>"
    },
    "name": "arcgis_request"
  }
}

Input Schema

Name	Required	Default
`path`	Yes
`method`	No	GET
`params`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.12.0Oct 23, 2026

TDQS

B3/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It mentions the configured token but does not disclose whether requests can mutate data, how the method affects safety, whether errors are surfaced, or what happens with POST versus GET; the examples include a job submission but no warning about side effects.

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 front-loaded with a one-sentence purpose followed by compact, concrete examples. The examples are directly relevant and no sentence is wasted for a tool that must cover arbitrary ArcGIS endpoints.

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

Completeness2/5

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

For a low-level generic REST caller with no annotations and 0% schema description coverage, the definition is missing critical context: method semantics, mutation/safety guidance, error behavior, and when to prefer this over the many sibling tools. The output schema exists, so return-value documentation is appropriately not repeated in the description.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must fully compensate. It gives useful path and params examples, but the method parameter is never explained—even though choosing GET versus POST is critical for a generic REST caller—and the null/default behavior of params is not clarified beyond the schema.

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

Purpose4/5

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

The description states a specific verb and resource: 'Call any ArcGIS Online REST endpoint with the configured token.' It is clear what the tool does, but it does not explicitly differentiate itself from the many higher-level sibling tools such as query_hk_data or build_map.

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 examples imply several usage scenarios—searching items, fetching item JSON, querying feature services, and submitting GP jobs—but there is no explicit guidance on when to use this generic tool versus the domain-specific siblings, nor any stated exclusions or prerequisites.

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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