Skip to main content
Glama

Decennial Census Tool

decennial_census_tool
Read-onlyIdempotent

Retrieve U.S. Decennial Census data for 2020 or 2010, including population counts, demographics by race/ethnicity, age, sex, and housing unit information at various geographic levels.

Instructions

Retrieve data from the U.S. Decennial Census (2020, 2010). Get complete population counts, demographics by race/ethnicity, age, sex, and housing unit data. The decennial census provides the most accurate population counts taken every 10 years.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesDecennial Census year: "2020" or "2010"
datasetNoDataset: "pl" (redistricting data, default for 2020), "dhc" (demographic and housing), "sf1" (summary file 1, default for 2010)
variablesYesCensus variable codes to retrieve. Common: P1_001N (total pop), P1_003N (White), P1_004N (Black), P2_002N (Hispanic), H1_001N (housing units)
geographyNoGeographic level for data aggregationstate
stateNoState FIPS code (required for county, tract, block group, place)
countyNoCounty FIPS code (required for tract, block group)
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds context about dataset accuracy and decennial frequency, which supplements the annotations without contradiction. It does not detail rate limits or other behaviors, but annotations cover safety adequately.

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?

The description is two sentences, front-loading the main purpose exactly. It uses efficient language with no waste, listing key data types and examples.

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?

For a read-only data retrieval tool with 6 parameters fully described in the schema and annotations present, the description covers purpose and data types adequately. No output schema is needed for simple retrieval. It is complete enough for the agent to use effectively.

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 coverage is 100%, so parameters are well documented with descriptions, enums, and patterns. The description adds common variable codes (e.g., P1_001N) and dataset meanings, but this is marginal beyond the schema. A baseline 3 is appropriate.

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 retrieves data from the U.S. Decennial Census, specifying the years (2020, 2010) and data types (population counts, demographics, housing units). It implicitly distinguishes from sibling tools like ACS (more frequent) and population estimates (intercensal) by emphasizing decennial census as the most accurate and every-10-years count.

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

Usage Guidelines3/5

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

The description implies usage for accurate decennial data but does not explicitly contrast with alternatives like acs_data_tool or population_estimates_tool. No when-to-use or when-not-to-use guidance is provided, leaving comparison to the agent.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mattpodwysocki/census-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server