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census-mcp

census-mcp

by mcpwright
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Look up a ZIP

lookup_zip
Read-only

Validate a US ZIP code against Census ZCTA to confirm it exists and get its official name and population.

Instructions

Confirm a ZIP maps to a Census ZCTA and return its name and population.

`zip_code`: a 5-digit US ZIP. A good first call to validate a ZIP before
asking for more detail. Returns the ZCTA, Census area name, total population,
and the ACS data vintage. ZIP ≈ ZCTA; ~2% of ZIPs have no ZCTA and error.

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": {
      "zip_code": "<zip_code>"
    },
    "name": "lookup_zip"
  }
}

Input Schema

NameRequiredDescriptionDefault
zip_codeYes

Output Schema

NameRequiredDescriptionDefault
nameNoCensus name for the area, e.g. 'ZCTA5 90069'
zctaYes5-digit ZIP Code Tabulation Area
vintageYesACS 5-year data vintage (end year)
populationNoTotal population (ACS 5-year estimate)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.5/5.0
Behavior4/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description adds valuable behavioral context: the ~2% error rate for ZIPs without ZCTAs and the return of the ACS data vintage. This helps the agent anticipate edge cases.

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-loaded with the core purpose. It includes a param note and caveat without excessive detail, though the structure is slightly dense with multiple ideas in a few sentences.

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 simple single-parameter read-only tool with an output schema available, the description covers purpose, parameter, usage context, and error behavior. Nothing critical is missing.

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

Parameters5/5

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

The schema provides no description for zip_code (0% coverage), but the tool description fully explains it as a 5-digit US ZIP and its role in validation. This completely compensates for the schema gap.

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 the tool confirms a ZIP maps to a Census ZCTA and returns its name and population, using a specific verb and resource. This distinguishes it from sibling tools like get_income or find_zips.

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?

The description provides clear usage context by calling it 'a good first call to validate a ZIP before asking for more detail.' However, it doesn't explicitly name alternatives or state when not to use this tool.

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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