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city-data-mcp

Official

Query Building Permits

query_permits

Retrieve 5-year county-level building permit trends across US cities to assess development activity or slowdowns.

Instructions

Building permit trends from the Census Bureau's Building Permits Survey. US only. Shows 5-year trend (2020-2024) of permits and housing units authorized at the county level.

52 cities available. Rising permits = development activity; declining = slowdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity name (e.g., 'Austin', 'Phoenix', 'Seattle')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden; it discloses the data source, geographic limit (US only), granularity claim, and time window (2020-2024), which is genuinely useful. It says nothing about data freshness, caching, pagination, or return shape, and the 'county level' claim sits oddly against a city-only parameter.

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

Conciseness4/5

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

Two short, front-loaded paragraphs with no filler; the source and scope come first and availability second. Slight redundancy/ambiguity around cities vs. county-level output keeps it from a 5.

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?

No output schema or annotations exist, so the description does the heavy lifting and mostly succeeds: source, scope, timeframe, and dataset size are all covered. The unresolved city-vs-county granularity is the one real gap for an agent deciding whether the result matches its need.

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 100% for the single 'city' parameter, so the baseline is 3. The description adds the useful constraint '52 cities available', but the stated county-level granularity conflicts with the city-only input rather than clarifying it.

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?

Names a specific resource (building permit trends) with source (Census Bureau Building Permits Survey) and scope (US only, 5-year 2020-2024 trend). This clearly separates it from siblings like query_housing or query_city_data, though it never explicitly names the adjacent alternative.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance relative to siblings such as query_housing, query_city_data, or query_economics. The line 'Rising permits = development activity; declining = slowdown' is interpretation help, not selection guidance.

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