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Data Montgomery

by io.github.pipeworx-io
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Montgomery Datasets

montgomery_datasets
Read-onlyIdempotent

Search the Montgomery County, MD open-data catalogue (data.montgomerycountymd.gov) for datasets by keyword. Returns dataset names, descriptions, and Socrata resource ids to use with montgomery_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datasets (1-100, default 20).
queryNoKeyword(s).
offsetNoOffset for paging.
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-data-montgomery-api-key",
+    "query": "building permits"
+  },
+  {
+    "_apiKey": "your-data-montgomery-api-key",
+    "limit": 10,
+    "query": "crime incidents"
+  }
+]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the description does not need to repeat safety. It adds value by explaining returned data includes resource IDs for use with montgomery_query, clarifying the output's purpose. No contradictions.

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?

Two sentences, zero fluff. Front-loaded with purpose and action. Every word is necessary.

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

Completeness5/5

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

For a search tool with thorough annotations and full schema coverage, the description is complete. It explains output (dataset names, descriptions, IDs) and connects to a sibling tool. No gaps given the tool's straightforward nature.

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

Parameters4/5

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

Schema coverage is 100% with descriptions for all 4 parameters. The description adds context: query is the search term, limit and offset for paging, _apiKey is optional. This goes beyond the schema by explaining the return format in relation to parameters.

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 it searches the Montgomery County open-data catalogue by keyword, returns dataset names, descriptions, and Socrata resource IDs. This distinguishes it from siblings like montgomery_query (which queries a specific dataset) and montgomery_recent (recent datasets).

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?

Description explicitly mentions use with montgomery_query, providing a clear workflow. It implies the purpose (search before query), but does not list when not to use or alternatives. Sibling context shows other dataset tools, but no explicit exclusions.

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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