India's District Intelligence API for research, reporting, policy, AI, and data products. Access production-ready district profiles, indicators, and geospatial intelligence through REST APIs and MCP tools—without scraping, cleaning, or stitching datasets together.
Join the early-access list — what you tell us you need shapes what gets built first.
One API. Hundreds of district indicators.
Multi-variate analysis with one API call — demographics, health, credit, and climate in a single response. Explore the shape of it below.
GEThttps://api.spatialindia.com/v1/districts/thane
{
"district": "Thane",
"state": "Maharashtra",
"slug": "thane",
"geography": {
"area_sqkm": 4214,
"density_per_sqkm": 2624
},
"demographics": {
"population": 11060148,
"literacy_rate": 84.5,
"sex_ratio": 886,
"urban_share_pct": 77
},
"health": {
"child_stunting_pct": 33.7,
"institutional_births_pct": 94.2,
"women_health_insurance_pct": 12.7
},
"economy": {
"msme_per_1000": 28.4,
"credit_per_capita_inr": 214650,
"credit_growth_5yr_pct": 11.2,
"credit_trajectory": "steady_growth"
},
"meta": {
"sources": [
"census_2011",
"nfhs5",
"udyam",
"rbi_bsr",
"cvi"
],
"dataset_version": "2026.07",
"boundary_vintage": "808-districts"
}
}Sample response — illustrative; the final schema may differ. Every value carries its source and vintage, so you always know what you're reading.
curl https://api.spatialindia.com/v1/districts/thane \ -H "Authorization: Bearer $SPATIAL_INDIA_KEY" # One call, every domain — demographics, health, credit, climate curl "https://api.spatialindia.com/v1/rankings?metric=credit_growth_5yr&state=maharashtra&limit=10" \ -H "Authorization: Bearer $SPATIAL_INDIA_KEY"
SDKs in Python and JavaScript at launch. Plain REST if you'd rather keep it simple.
Everything you'd build yourself. Already built.
Behind every indicator: hundreds of hours of crosswalking, name-matching, and boundary reconciliation across 10+ official sources. You get the result — one clean schema.
Everything, already stitched together.
13 domains, one schema, one call. Every dataset crosswalked to the current 800+ district geography and versioned.
Demographics
Population, sex ratio, urbanization — the baseline for every model.
Health & Nutrition
Stunting, anemia, institutional births for healthcare planning.
Health Coverage
Insurance and vaccination coverage for underwriting and outreach.
Education
Literacy and schooling to segment markets and target programs.
Women & Gender
Gender gaps in literacy, work, and safety — lived-experience signals.
Infrastructure
Sanitation, electricity, water, banking access for site selection.
Governance
Judicial backlog and case delay as institutional-quality proxies.
Safety & Crime
Seven crime rates per lakh for risk scoring and safety indices.
Climate & Environment
Climate vulnerability for ESG and physical-risk assessment.
Employment
Worker participation and MGNREGA demand as distress signals.
Economy
MSME density, bank credit, night lights — the economic pulse.
Land & Agriculture
Holding size, irrigation, land equity for agri and credit models.
Lifestyle & Diseases
NCD and lifestyle indicators for insurance and pharma.
+More shipping regularly
UDISE+ education, HMIS health, crop production, PM2.5, elections — new sources land as new fields in the same schema. Additive, versioned, never breaking.
Your agent doesn't read PDFs. Neither should you.
Use Spatial India from Claude, Cursor, or your own agents. Instead of calling endpoints, agents invoke capabilities through our MCP server.
“Find districts in Maharashtra with high literacy but low healthcare access.”
search_districts(state="Maharashtra", literacy="top_quartile", health_access="bottom_quartile")
get_district_profile("thane")
compare_districts(["thane", "pune", "nashik"], domain="health")
Returns a structured answer: 7 districts, ranked, with the exact indicators that qualified them — ready for your agent to act on.
An API you already know how to use.
A small, stable surface you can learn in five minutes — and a data model you can see before you sign up. Proposed v1 surface; details may change before launch.
data model
District ├── demographics # population, literacy, sex ratio ├── health # NFHS-5: stunting, anemia, coverage ├── education # literacy, schooling ├── women_gender # gender gaps, safety ├── infrastructure # sanitation, electricity, banking ├── governance # judicial backlog, delay rates ├── safety # NCRB crime rates per lakh ├── climate # vulnerability index ├── employment # workers, MGNREGA ├── economy # MSME, RBI credit, night lights ├── agriculture # holdings, irrigation, land equity └── meta # sources, versions, estimation flags
Built for research, reporting, and policy.
If your product or analysis touches Indian geography, this is the layer underneath it.
The first cohort shapes the product.
First in line
When access opens, invites go out in waitlist order. Early signups hear first.
Early-access pricing
Waitlist members get first claim on launch pricing offers when the API goes live.
Shape the API
This page exists to learn what you need. The endpoints and datasets the waitlist asks for get built first.
Small first cohort
We plan to start with a small cohort so feedback loops stay tight and every use case gets heard.
Simple tiers, no surprises.
Free
Evaluate and prototype
Developer
Ship to production
Enterprise
Scale with guarantees
Pricing finalized at launch. Waitlist members get early-access pricing. Tiers and terms subject to change without notice.
Frequently Asked Questions
We’re gauging demand right now — the interest on this page decides how fast the API gets built. Waitlist members hear first, and the first cohort will be invited in signup order. We won’t promise dates until we can keep them.
Every dataset on Spatial India: Census 2011, NFHS-5, RBI bank credit (quarterly, through 2026), MSME/Udyam 2026, NJDG 2024, NCRB 2022, NASA VIIRS night lights 2015–2024, Agricultural Census, climate vulnerability, and more — 85+ datasets across 13 domains, all crosswalked to the current 800+ district geography. Each response carries the source vintage, so you always know what you’re reading.
Yes — the sources are open government data. What you’re buying is the pipeline: hundreds of hours of crosswalking, name-matching, boundary reconciliation, and estimation, maintained as one stable schema across every source. We sell the ETL, not the data. You skip straight to building.
MCP (Model Context Protocol) is the open standard for connecting AI agents to tools. Our MCP server exposes the same capabilities as the REST API — so Claude, Cursor, and your own agents can call search_districts() or compare_districts() directly, without you writing glue code.
Every dataset release is immutable and tagged (e.g. 2026.07). Your integration pins a version; new source drops — including Census 2027 — arrive as new versions within days of release, never as silent changes under your feet.
Yes. The Developer tier includes CSV and bulk endpoints for the same curated, crosswalked data, and Enterprise adds private bulk delivery. REST, MCP, and bulk all draw from one schema.
A free tier for evaluation is planned at launch. Production pricing will be finalized at launch — waitlist members get first claim on early-access pricing before public rates apply. All pricing and tier details are subject to change until launch.
The platform is built on open government data (NDSAP), so your usage rights are clean. Free-tier responses require attribution to Spatial India; paid tiers don’t. Made in India, with open data you can trust.
Early Access
Join the waitlist — the use cases we hear decide what gets built first, and you'll know the moment access opens.