Size any US market in seconds, not weeks.

Establishments, employment, payroll, GDP, and occupation wages for every NAICS industry — cross-referenced from Census, BEA, BLS, IRS, and SEC filings, and queryable from the web app, the API, or your AI assistant over MCP.

Open the app See how it works

TAM Tool Economy Map Occupations Industry Segments EDGAR Companies Sources

US private-sector establishments by NAICS sector · nation · Census CBP 2022 · click any block to drill down

2,196

NAICS segments, sector to 6-digit

925

metro & micro areas (CBSA)

800+

SOC occupations with wages

federal sources, cross-referenced

What you get

A week of analyst work, already done.

The data a market-sizing analyst would spend a week assembling — downloaded, normalized, and cross-referenced into one queryable layer.

NAICSEvery industry segment

All 2,196 codes from sector (2-digit) down to industry (6-digit). Drill in, roll up, compare.

GEONational, state, and metro

Nation, 50 states + DC + territories, and 925 CBSAs (Census metro/micro areas).

SIZEFirmographics by size band

Establishment counts, employment, and payroll by employee-size band — 9 CBP bands, 24 SUSB bands.

GDPGDP and I-O flows

BEA value-added and gross output by industry, plus the Use table so you can trace buyers and suppliers.

SOCWages by occupation

BLS OEWS — median, percentile, and mean wages for every SOC occupation × industry pair.

EDGARPublic comps

SEC EDGAR XBRL financials for public SaaS and small-cap companies mapped to their NAICS segment.

MCP server

Ask your AI assistant. Get sourced numbers back.

TAM Tool ships an MCP server, so Claude — or any MCP client — can pull market data straight into the conversation instead of guessing.

12 query tools: segment profiles, occupation wages, buyer/supplier flows, SaaS comps, expense structures
Same data layer as the web app — every answer cites its source and vintage
Works with Claude Desktop, Claude Code, and any MCP-compatible client

Read the setup docs →

claude — connected to tam-mcp

> How big is the US landscaping services market,
  and who does the work?

⏺ get_segment_summary(naics_code: "56173")
  └ 122,477 establishments · 654k employees
    $27.2B annual payroll · Census CBP 2022

⏺ top_occupations_for_industry(naics: "5617")
  └ 37-3011 Landscaping Workers · median $37,360
    · BLS OEWS May 2024

How it works

Pick a segment. See the whole picture.

Choose a segment, geography, and slice — the tool shows size, growth, competitive structure, and unit economics side by side.

Start at a sector, drill to an industry

Interactive treemap by NAICS. Click any block to drop a level and the data re-aggregates.

Switch geography

Flip between nation, state, and CBSA without changing queries. Choropleth for state-level views.

Cross-reference the full picture

Establishment counts, payroll, occupation wages, GDP, supplier/buyer flows, and public comps for the same segment, all on one page.

Cite the source

Every number links back to the government source and the vintage of the data, so you can defend the estimate in a deck.

Data sources

All public. All cited. No black boxes.

Every dataset comes from a federal statistical agency and is updated on the publishing agency's own cadence.

Census CBP 2022

County Business Patterns — establishments, employment, and payroll by NAICS, size band, and geography.

Census SUSB 2022

Statistics of US Businesses — firm and establishment counts with finer 24-bin size bands and receipts.

BEA GDP by Industry

Value added and gross output for every BEA industry, reconciled to NAICS.

BEA Input-Output

Use Table — the commodity × industry matrix of who sells what to whom, in millions of dollars.

BLS OEWS May 2024

Occupational Employment and Wage Statistics — wages and employment for 800+ occupations across industries.

IRS SOI Corporate

Publication 16 — income, deductions, balance-sheet, and tax data aggregated by industry from actual tax returns.

SEC EDGAR XBRL

Public-company financials direct from 10-K and 10-Q filings, mapped to NAICS via the SIC crosswalk.