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zencity-product

city-data-mcp

Official

Query City Budget

query_budget

Retrieve municipal budget data for US and UK cities, including total spending, per-capita amounts, category breakdowns, and UK council tax Band D figures.

Instructions

City government budget data for a city in the US or UK.

US: Published municipal budgets — total budget, per-capita spending, category breakdown (30 cities). UK: Local authority spending — council tax Band D, total spending, category breakdown (11 cities). CA: Not yet available.

Country auto-detected or specify with country parameter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity name (e.g., 'NYC', 'Manchester', 'Denver')
countryNoCountry code. Auto-detected from city name if omitted. Required for ambiguous cities like London, Birmingham, Richmond, Hamilton, Cambridge, Windsor.

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 carries the full behavioral burden. It discloses meaningful coverage constraints: US supports 30 cities, UK 11 cities, CA not available, which is genuinely useful scoping information. However, it says nothing about permissions, error behavior for unsupported cities, or data recency.

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?

The description is compact and front-loads the resource, then organizes availability by country in parallel structure. The final sentence about auto-detection duplicates schema content, but overall there is little waste.

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

Completeness3/5

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

For a read-only data query with a fully documented two-parameter schema, the description covers coverage scope adequately. It omits any sense of return structure (no output schema exists), pagination, or fallback behavior for unsupported cities, leaving some gaps for an agent to call confidently.

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%, so the schema already documents both parameters including the ambiguous-city list for the country field. The description's mention of country auto-detection reiterates what the schema already states, adding little beyond the structured fields. Baseline 3 is appropriate.

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 the tool returns city government budget data and enumerates the specific fields available (total budget, per-capita spending, category breakdown, council tax Band D). This clearly distinguishes it from sibling query_* tools, though the opening 'City government budget data' is somewhat generic before the specifics arrive.

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?

The description provides no when-to-use guidance, no conditions distinguishing it from siblings like query_city_data or query_economics, and no alternatives named. The country coverage notes imply availability constraints but do not tell the agent when this tool is the right choice.

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