Location Compare

x402

Location Compare is a paid API for AI agents from agent-vending-production.up.railway.app, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-11).

Compare 2–10 U.S. geographies side-by-side across up to 16 Census demographic, income, education, housing, and workforce metrics in a single call.

Price / call$0.01

Seller volume →—

Success—

StatusUnknown

How this service works

Pay-per-call machine utilities for autonomous agents.

Output

Returns a structured side-by-side table of requested metrics for each input geography, optionally including U.S. national and state-level benchmark values and national percentile rankings for each metric, enabling direct quantitative comparison across locations.

Example use cases

City relocation decision support

“I'm deciding between moving to Raleigh NC, Charlotte NC, and Richmond VA — can you compare them on median household income, homeownership rate, unemployment rate, and the percentage of residents with a bachelor's degree or higher, with U.S. benchmarks included?”

County market entry analysis

“We're evaluating three counties for a new retail location: Maricopa County AZ, Travis County TX, and Mecklenburg County NC. Compare them on median household income, poverty rate, population, and labor force participation rate so we can decide where the market opportunity is strongest.”

Zip code neighborhood comparison

“Compare zip codes 10001, 11211, and 10025 in New York on median home value, median gross rent, per capita income, and the share of residents with a bachelor's degree or higher — and show me how they rank against each other.”

Technical details

Endpoint

POSThttps://agent-vending-production.up.railway.app/v1/location-compare?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need a structured, multi-metric side-by-side comparison of 2–10 specific U.S. locations rather than a profile of a single place, a similarity search, or a ranked site-selection query. It is ideal when the user already knows which locations to compare and wants normalized Census statistics with optional national benchmarks and percentiles in one call, rather than making separate lookups and aligning data manually.

Side effects

Fewer than 2 or more than 10 locations provided — request rejected
Mixed geography types (e.g. state + county) without allow_mixed_geography_types=true — request refused without charge
Unresolvable location name or GEOID — returns error for that geography
Census data unavailable for a given tract or ZCTA — metric returned as null
Invalid metric name in custom list — validation error returned

Input

Schema · Request body

Field	Type	Description
metrics	—	Default CORE_COMPARE (16 metrics) or a subset list
locations	array	2-10 geographies of the same type (mixed types only with allow_mixed_geography_types)
include_benchmarks	boolean	U.S./state reference values and national percentiles (default true)
allow_mixed_geography_types	boolean	Default false (mixed types refused, not charged)

Output

Schema · Response

{
  "type": "json",
  "example": {
    "status": "OK",
    "product": "location_compare",
    "summary": {
      "largest_differences": [
        {
          "lowest": "San Diego County, California",
          "metric": "median_age",
          "highest": "Ventura County, California",
          "difference": 2.3,
          "difference_unit": "years",
          "national_percentile_spread": 14
        }
      ]
    },
    "locations": [
      {
        "name": "Ventura County, California",
        "geoid": "06111",
        "geo_type": "county"
      },
      {
        "name": "Orange County, California",
        "geoid": "06059",
        "geo_type": "county"
      },
      {
        "name": "San Diego County, California",
        "geoid": "06073",
        "geo_type": "county"
      }
    ],
    "comparison": [
      {
        "unit": "usd",
        "lowest": {
          "geoid": "06073",
          "estimate": 102285
        },
        "metric": "median_household_income",
        "values": [
          {
            "geoid": "06111",
            "moe_90": 1391,
            "estimate": 107327,
            "national_percentile": {
              "percentile": 96.91
            }
          },
          {
            "geoid": "06059",
            "moe_90": 986,
            "estimate": 113702,
            "national_percentile": {
              "percentile": 98.03
            }
          },
          {
            "geoid": "06073",
            "moe_90": 899,
            "estimate": 102285,
            "national_percentile": {
              "percentile": 95.98
            }
          }
        ],
        "highest": {
          "geoid": "06059",
          "estimate": 113702
        },
        "comparison_status": "SIGNIFICANT_DIFFERENCE",
        "largest_difference": {
          "difference": 11417,
          "difference_unit": "usd",
          "significance_90": {
            "significant": true
          },
          "percent_difference_vs_lowest": 11.16
        }
      }
    ],
    "provenance": [
      {
        "dataset": "acs/acs5/profile",
        "provider": "census_acs",
        "release_year": 2023
      }
    ],
    "data_vintage": {
      "label": "ACS 5-Year 2019-2023",
      "dataset": "ACS 5-Year",
      "release_year": 2023
    },
    "vintage_check": {
      "release_year": 2023,
      "same_vintage": true
    }
  }
}

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