# NYC Schools & Education AI Agent Connect

> NYC Schools & Education MCP provides keyless access to New York City Department of Education records. Your AI client can pull school quality metrics, chronic absenteeism statistics, enrollment capacity, and high school performance data using 6-digit DBN identifiers. It works with any MCP-compatible client like Claude, Cursor, or Windsurf.

## Overview
- **Category:** education
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_bUIVk7ieDGEY0IsJaTKbPFQdY66dN4WGApyogKPJ/ai-agent-connect
- **Tags:** new-york, nyc, schools, doe, attendance, absenteeism, enrollment, high-school

## Description

You can pull specific NYC Department of Education records directly into your AI workflow. Instead of hunting through web portals, you use this MCP to query school quality metrics, attendance trends, and enrollment capacity. You can look up specific high school performance ratings or browse the public high school directory by borough. Most data is tied to the 6-digit District Borough Number (DBN), such as 04M479. This tool covers attendance data from the 2016-17 school year through 2022-23, while school quality report years span from 2016 to 2025. It is built for anyone needing hard numbers on NYC school performance, equity, or capacity without managing complex API credentials.

## Tools

### get_high_school_performance
This tool pulls 2019-20 School Quality Guide ratings for a specific high school. It provides enrollment, survey ratings, ELA and Math benchmarks, and demographic shares using a DBN.

### get_citywide_absenteeism
This tool returns citywide chronic absenteeism and attendance statistics. It provides end-of-year data broken down by grade and category for a specific school year.

### get_school_chronic_absenteeism
This tool retrieves attendance and chronic absenteeism data for a single school. It breaks down total days, attendance rates, and chronic-absent counts by grade and category via DBN.

### list_high_schools
This tool provides a directory of NYC DOE public high schools. You can filter the results by borough or partial school name.

### search_enrollment_capacity
This tool checks building and organization enrollment capacity and utilization. You can filter by district, organization name, or building name.

### search_school_quality_metrics
This tool searches NYC DOE School Quality Report metrics. You can find specific data points by using a school name or DBN, and filter by report year or metric variable.

## Prompt Examples

**Prompt:** 
```
Show me the chronic absenteeism for school 04M479 in 2020-21.
```

**Response:** 
```
get_school_chronic_absenteeism with dbn: "04M479" and year: "2020-21" returns the end-of-year attendance and chronic-absent rows for that school, broken down by grade and category.
```

**Prompt:** 
```
What metrics did a school report in 2024?
```

**Response:** 
```
search_school_quality_metrics with the dbn (or a school name) and report_year: "2024" returns each metric row with its display name, value and student count.
```

**Prompt:** 
```
What is the citywide chronic absenteeism rate?
```

**Response:** 
```
get_citywide_absenteeism returns the citywide end-of-year attendance and chronic-absent statistics by grade and category.
```

## Capabilities

### Attendance Analysis
Your agent can compare chronic absenteeism rates between specific schools or across the entire city.

### School Quality Audits
Your AI client can pull specific performance metrics and benchmark percentages for individual schools.

### Capacity Planning
Your agent can check enrollment versus target capacity at the building, organization, or district level.

### High School Research
Your AI client can browse high school directories and pull specific performance guides for individual campuses.

## Use Cases

### Tracking Absenteeism Trends
An analyst uses the agent to compare school-specific chronic absenteeism against citywide averages.

### High School Selection
A researcher queries high school performance ratings and demographics for specific DBNs.

### Capacity Audits
A district planner checks building utilization and enrollment targets via the agent.

### Metric Comparison
A journalist pulls specific School Quality Report metrics for multiple schools to compare performance.

## Benefits

- Access NYC DOE data without needing an API key.
- Query specific school metrics using 6-digit DBN identifiers.
- Pull historical attendance data spanning multiple school years.
- Get building-level enrollment and utilization stats.

## How It Works

Connecting to this MCP gives your AI client immediate access to NYC DOE datasets.

1. Connect your MCP-compatible client to Vinkius.
2. Select the NYC Schools & Education MCP from the catalog.
3. Ask your agent a question using a school name or DBN.
4. The agent executes the corresponding tool to fetch live data.
5. Receive the raw metrics or statistics directly in your chat interface.

## Frequently Asked Questions

**Do I need an API key to use this?**
No. This MCP provides keyless access to the NYC Department of Education records.

**How do I identify a specific school?**
You should use the 6-digit District Borough Number (DBN), such as 04M479, to ensure accuracy.

**What years of attendance data are available?**
Attendance data covers school years from 2016-17 through 2022-23.

**Can I filter high schools by location?**
Yes. You can filter the high school directory by borough or by a partial school name.

**Which AI clients can use this MCP?**
You can use this with any MCP-compatible client, including Claude, Cursor, and Windsurf.

**Do I need an API key?**
No. NYC Open Data serves all public datasets anonymously over its SODA API (data.cityofnewyork.us). This MCP defines no credentials and needs nothing configured.

**How are schools identified?**
By their 6-digit DBN code (e.g. "04M479"). get_school_chronic_absenteeism and get_high_school_performance require the DBN; the other tools can search by school name (partial match).

**What year formats do the education datasets use?**
School Quality Reports use 4-digit report years (2016–2025). Attendance and absenteeism datasets use school years in "YYYY-YY" form ("2016-17" through "2022-23"). The high school directory and the performance ratings are the 2019-20 editions.