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Glama

Data Boston

by io.github.pipeworx-io

Boston Query

boston_query
Read-onlyIdempotent

Query any City of Boston datastore resource (data.boston.gov, CKAN) by its resource id (a UUID). Supports a free-text q, exact-match filters (field→value), sort ("field desc"), limit and offset. Use boston_datasets to find a resource id, or boston_recent for the common ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree-text search across columns.
sortNoSort clause, e.g. "OCCURRED_ON_DATE desc".
limitNoMax rows (default 100, max 1000).
offsetNoRow offset for paging.
filtersNoExact-match filters as a JSON object, e.g. {"district":"B2"}.
resource_idYesCKAN datastore resource id (UUID), e.g. "b973d8cb-eeb2-4e7e-99da-c92938efc9c0".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "filters": {
+      "district": "B2"
+    },
+    "limit": 100,
+    "resource_id": "b973d8cb-eeb2-4e7e-99da-c92938efc9c0",
+    "sort": "OCCURRED_ON_DATE desc"
+  },
+  {
+    "limit": 50,
+    "q": "pothole",
+    "resource_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
+  }
+]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating safe query behavior. Description adds feature details (free-text, filters, sort, pagination) but no behavioral surprises or 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 concise sentences with no fluff. Every sentence earns its place: first states core function, second lists supported features and guides to sibling tools.

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?

Covers purpose, key features, and usage guidance. With schema providing full parameter details and annotations covering safety, description is complete enough. Lacks mention of rate limits or empty result behavior but acceptable given context signals.

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?

Input schema has 100% coverage with descriptions for each parameter. Description summarizes the key parameters but does not add meaning beyond what schema provides, meeting baseline.

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?

Description clearly states verb 'Query' and resource 'City of Boston datastore resource by resource id (UUID)'. It distinguishes from sibling tools by referencing boston_datasets and boston_recent for finding resource ids.

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?

Explicitly advises using boston_datasets to find a resource id and boston_recent for common ones, providing clear alternative usage. Does not explicitly state when not to use, but context is sufficient.

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

All Data Boston toolsInspect
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TDQS

A4.1/5.0
Disambiguation3/5

Several tools occupy adjacent territory: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same router, ask_pipeworx_beta is currently an exact duplicate, and there are multiple polymarket-related tools. The descriptions are unusually explicit and cross-reference when to use which, which keeps this from scoring lower.

Naming Consistency4/5

All tool names use lowercase snake_case and group into recognizable families (boston_*, pipeworx_*, polymarket_*), giving the set a consistent feel. However, the set mixes verb_noun names, bare verbs like remember/forget, and adjective_noun phrases like recent_changes, so it is not a strict verb_noun pattern throughout.

Tool Count2/5

At 34 tools this exceeds the 25+ threshold and feels bloated for a server with the narrow name "Data Boston"—only three tools directly concern Boston data, while the rest cover general research, prediction markets, subscription management, memory, AI visibility, and npm auditing. Most tools have a purpose, but the overall surface is not well-scoped.

Completeness4/5

For the broad data-access purpose, coverage is strong: routing, grounded verification, entity profiles, comparisons, change tracking, entity resolution, discovery, monitoring, memory, and Boston datasets are all represented. Minor gaps exist, such as no subscription update operation, no explicit fetch-by-citation tool, and limited boston_recent coverage, but agents can work around them.

Resources