For healthcare & life sciences

Compliance geography for pharma, providers, and payers

U.S. counties, ZIP code areas, and custom catchments — joined to Census demographics, with workspace-isolated datasets for sensitive provider data. Use it for patient-access mapping, network-adequacy reviews, dispensary-proximity compliance, or any 'who lives near what' question.

What it looks like

A typical workflow for healthcare & life sciences teams. Each line is one operation; together they take a few minutes and produce a published map plus a downloadable dataset.

# "Are we within 5 minutes' walk of any pediatric clinic?"

mcp.call("bulk_match_addresses", { records: our_dispensaries })
  → 412 sites geocoded

// Fan out 5-minute walk-time areas across all sites:
const walkPolygons = await Promise.all(sites.map(s =>
  mcp.call("geo_isochrone", { point: [s.lng, s.lat], minutes: [5], profile: "walking" })
));

mcp.call("geo_intersect_dataset", {
  polygons: walkPolygons,
  dataset: "pediatric_clinics_spreadsheet",
})
  → 38 dispensaries within a 5-minute walk of a clinic

mcp.call("create_report", {
  layer: { polygons: walkPolygons, highlight: violations },
  public: false,
  embed_origins: ["compliance.ourdomain.com"],
})
  → secure embed iframe · no Maps MCP footer · no public URL

What you can build

Dispensary / clinic proximity compliance — geo_isochrone + geo_intersect_dataset answers 'how many pediatric clinics are within a 5-minute walk of every dispensary?' in one chained call.
Patient-access mapping — Upload your patient roster, bucket by ZIP code, render a service-area heatmap. PNG ready for board decks. Your spreadsheet stays workspace-private.
Provider-network gap analysis — geo_hotspot finds underserved clusters. interpret_hotspot has Claude write the narrative — 'Cold spots cluster along the I-95 corridor where...'
Health-equity demographics overlay — Pull Census race / income / age tables, join to your service area, build a two-variable map showing where need intersects with under-coverage.
Origin-allowlist embeds for patient-health maps — Pro tier locks embed iframes to your domain only. Maps live on compliance.yourbrand.com, never on mapsmcp.com.

The tools you'd actually use

bulk_match_addresses
Patient or provider address → county + latitude/longitude, batched

shapes_within_radius
Find every clinic within X meters of a point

geo_isochrone
Walk / drive / cycle time around any facility

geo_intersect_dataset
Records inside any polygon (catchment / district / radius)

census_acs
Demographic context for any geography (county, congressional district, ZIP code, tract)

disaggregate_acs
Push Census tract-level demographics down to hospital service areas or custom catchments

geo_hotspot
Statistical hot-spot clustering of any metric

render_map_bivariate
Two-variable map — e.g. need × access

interpret_hotspot
Claude narrates the cluster pattern

How it differs from the alternative

vs. Esri Health Solutions: no $50,000 seat license, no two-week onboarding — get a publishable map in minutes. vs. building in-house: every dataset is workspace-isolated by default, with origin-allowlist embeds for internal patient maps. vs. ChatGPT + Google Sheets: your geography is real and versioned, not invented by the model.

Pricing for healthcare & life sciences teams

Compliance teams typically run on Pro ($50/month) for the embed-origin allowlist and up to 25 sub-workspaces. Larger health systems should email about Enterprise. Full pricing details.

From data file to provider-network map in 5 calls.

Free tier — evaluate before any credit card is needed.

Get an API key

The same toolkit also covers grassroots organizing platforms & campaign tooling · civic tech & journalism · real estate & property tech · retail, consumer brands & site selection · insurance & risk modeling · logistics, delivery & field service · research, academia & think tanks · pollsters & survey research firms — one U.S.-geography surface for any team whose question comes down to where.