From data to decisions
Parents don’t want “ask anything about schools.” They want “help me not mess this up.” SchoolScope AI turns multi-dimensional data into personalized school decisions.
Decision Mode
Not a blank chat box — a guided flow that asks about your kid, then matches schools to your family’s actual priorities.
Then you get a personalized match
Your child thrives with challenge — Canyon has 58% exceeding standard with strong parent involvement. The smaller campus is great for quieter kids who need a supportive community.
+5.8pp growth G3→G5 means Clover is actively building kids up. Diverse student body aligns with your priority. 8 min drive.
Score 72, balanced across all factors. Walking distance. Good fit if you want solid academics without the lottery process.
Archetypes match families, not just numbers
Every school has a personality. Decision Mode maps your family’s priorities to the archetype that fits.
Kid is bored, needs ceiling raised. High exceeded %, strong top-end performance.
Kid needs to catch up. These schools add the most academic value year over year.
Balanced family priorities. No single weakness, consistently solid across all 6 factors.
Values community and belonging. Low absenteeism + suspension signals a healthy school culture.
Distribution: be where parents already ask
Parents already ask ChatGPT about schools. ChatGPT currently cites GreatSchools. Our MCP server makes SchoolScope the data source when parents ask AI anywhere — the school data complement to ATTOM’s 158M property records.
Search by name, city, ZIP, or district. Returns Scope Score, archetype, key stats.
Full profile: 6 score factors, spending breakdown, demographics, feeder pattern.
Schools within radius of lat/lng. Built for property listing context.
Side-by-side across all dimensions. 2–5 schools per call.
Pre-assembled school data for a location. One call, complete neighborhood picture.
District spending, avg scores, school count, performance distribution.
For AI developers
llms.txt (live now)
Machine-readable site description at /.well-known/llms.txt. AI crawlers can discover our data and methodology today.
OpenAPI spec (coming)
Full OpenAPI 3.0 spec. Auto-generate client SDKs in any language.
Tool-calling schemas
Function definitions for GPT, Claude, and Gemini. Copy-paste into your agent config.
LLM-optimized responses
Every response includes descriptions optimized for LLM consumption — not just raw numbers.
Get early access
Be first to try Decision Mode and connect your AI agent to SchoolScope data.