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 capabilities 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.

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Connect Nyc Schools Education to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Direct access to NYC Department of Education data for your agent.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

How Vinkius works: one connection, every tool, in any AI

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Complete set · 6 capabilities

The complete NYC Open Data capability set.

These are the exact actions your AI can choose when you ask it to work with NYC Open Data.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through NYC Open Data.

01
Get high school performance
This capability 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.
02
Get citywide absenteeism
This capability returns citywide chronic absenteeism and attendance statistics. It provides end-of-year data broken down by grade and category for a specific school year.
03
Get school chronic absenteeism
This capability 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.

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through NYC Open Data.

04
List high schools
This capability provides a directory of NYC DOE public high schools. You can filter the results by borough or partial school name.
05
Search enrollment capacity
This capability checks building and organization enrollment capacity and utilization. You can filter by district, organization name, or building name.
06
Search school quality metrics
This capability 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.

One connector, every AI

NYC Open Data works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put NYC Open Data to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of NYC Open Data, so you can see the experience inside your AI.

It does not authenticate your account with NYC Open Data. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

NYC Open Data Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_bUIVk7ieDGEY0IsJaTKbPFQdY66dN4WGApyogKPJ/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — NYC Open Data capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "nyc-schools-education-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_bUIVk7ieDGEY0IsJaTKbPFQdY66dN4WGApyogKPJ/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? How to give Claude access to NYC Open Data

See all the AI clients this connector works with ↑

Who it's for

Built for the work NYC Open Data owners hand off.

This MCP is built for professionals who need to query NYC education data without manual data scraping.

01
Education Researchers
They hand off data aggregation and trend analysis tasks to their agent.
02
Journalists
They use the agent to quickly pull school performance or absenteeism stats for reporting.
03
Equity Analysts
They task their agent with finding discrepancies in school quality or enrollment capacity.

FAQ

Questions NYC Open Data owners ask.

01
Do I need an API key to use this?
No. This MCP provides keyless access to the NYC Department of Education records.
02
How do I identify a specific school?
You should use the 6-digit District Borough Number (DBN), such as 04M479, to ensure accuracy.
03
What years of attendance data are available?
Attendance data covers school years from 2016-17 through 2022-23.
04
Can I filter high schools by location?
Yes. You can filter the high school directory by borough or by a partial school name.
05
Which AI clients can use this MCP?
You can use this with any MCP-compatible client, including Claude, Cursor, and Windsurf.
06
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.
07
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 capabilities can search by school name (partial match).
08
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.

Explore

More in Education

Connect NYC Open Data to Claude, Cursor, ChatGPT & more

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

Get high school performance

Get citywide absenteeism

Get school chronic absenteeism

List high schools

Search enrollment capacity

Search school quality metrics

Building your own app? The connector is yours to use.

NYC Open Data Connector

Claude Desktop

Education Researchers

Journalists

Equity Analysts

Do I need an API key to use this?

How do I identify a specific school?

What years of attendance data are available?

Can I filter high schools by location?

Which AI clients can use this MCP?

Do I need an API key?

How are schools identified?

What year formats do the education datasets use?

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