Curated public datasets that drop into your workspace with one call. Pre-joined to the right boundary, pre-sized for a free-tier evaluation, and every card links to a live sample map you can open right now. Skim, copy the snippet, paste into your MCP client.
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Every county's two-party vote shares + raw vote counts for the last three presidential cycles. Sourced from tonmcg/US_County_Level_Election_Results_08-24 (maintained, complete). Drop-in for swing analysis, turnout maps, and partisan-trend storytelling.
mcp.call("ingest_county_pres", { year: 2024 })
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Curated state and congressional-district results back through the late-Clinton-era races. Useful for time-series partisan analysis, vote-margin trend lines, and historical context overlays.
mcp.call("ingest_538_results", {
cycle: 2024,
race: "house", // also: "president", "senate"
})
Precinct-level 2024 presidential margin — 163,000 voting precincts across all 50 states plus Washington, DC. Sourced from the New York Times open precinct file. Ideal for the precinct-turnout-map newsroom story and any sub-county analysis.
mcp.call("ingest_nyt_precincts_2024", {
state: "nc",
rollup: "precinct",
})
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You bring Democratic / Republican / total vote counts per geography (congressional district, county, precinct, or state). We auto-derive margin, percentage margin, winning party, and publish a public report with diverging palette and auto-built methodology description. Works for presidential, senate, gubernatorial, House, state-legislative, and ballot-measure races.
mcp.call("ingest_election_results", {
election_name: "2024 U.S. House — general",
date: "2024-11-05",
race_type: "house",
jurisdiction: "United States",
target_collection: "us-cd119",
target_version: "tiger-2024",
rows: [
{ external_id: "0612", values: { votes_dem: 153021, votes_rep: 147803 } },
// ... one row per district
],
slug: "election-2024-house",
})
Universal partisan-baseline citation for any congressional-district analysis. Every campaign brief and every district-overperformance story cites this. The Cook Partisan Voting Index is anchored to the prior two presidential cycles plus the relevant Census apportionment.
mcp.call("ingest_cook_pvi", { congress: 119 })
Poole–Rosenthal ideology score for every House member and senator. The standard scholarly ideology spine. Useful for floor-vote analysis, ideology-vs-Partisan-Voting-Index scatterplots, and 'how moderate is my district?' narratives.
mcp.call("ingest_voteview", {
congress: 119,
chamber: "house",
})
Candidate-level campaign-finance ideology score for every federal candidate, aggregated to each congressional district. Donor-side ideology overlay — different signal than vote-based ideology since this captures the coalition that funded the campaign.
mcp.call("ingest_dime", { cycle: 2024 })
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Full programmatic access to the American Community Survey (the Census Bureau's demographic survey). Pick a variable code (B19013_001E = median household income, B01002_001E = median age, etc.), a boundary level, and a 5-year edition. We handle the Census API key, the geography hierarchy, and the workspace-dataset assembly.
mcp.call("census_acs", {
collection: "us-counties",
version: "tiger-2024",
year: 2023,
variables: ["B19013_001E"], // median household income
slug: "county-mhi-2023",
})
Take the crosstabs file you already produce and render a publication-grade regional, congressional-district, or county map. Statewide topline, regional vote intent, methodology coverage — embeddable in your client deliverable PDF or the press release page.
mcp.call("ingest_poll_crosstabs", {
pollster: "<your firm>",
field_date: "2026-05-07",
jurisdiction: "Michigan",
topline: { candidate_a_pct: 42, candidate_b_pct: 41 },
target_collection: "us-counties",
target_version: "tiger-2024",
rows: [
{ external_id: "26163", values: { candidate_a_pct: 38, candidate_b_pct: 49 } },
// ... one row per geography in the crosstab
],
slug: "<your-poll-slug>",
})
FEMA flood zones, National Interagency Fire Center wildfire perimeters, NOAA hurricane swaths, agency districts, your own field-office service areas. Anything that's a public GeoJSON file becomes a queryable, joinable workspace boundary set in one call.
mcp.call("ingest_geojson", {
url: "https://hazards.fema.gov/.../houston-zone-x.geojson",
collection: "fema_zone_x_hou",
collection_name: "FEMA Zone X — Houston",
level: "hazard",
version: "nfhl-2026-05",
})
ingest_dataset +
ingest_geojson tools. We're also happy to add curated ingestors for
sources our customers ask about — email [email protected]
with what you need.
The cards marked Premium call are tools where each call has real cost on our side (multi-MB ingest, Census geocoder, external rate-limited APIs, large CPU renders). They count against your tier's premium-call cap rather than your standard-call cap. Free tier includes 0 premium calls; Starter gets 25/month; Pro gets 250/month. See /pricing for the full breakdown.
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