Education Data

Education Find Schools

education_find_schools

Read-onlyIdempotent

Find US K-12 PUBLIC SCHOOLS by state, with optional city or name filter. Keyless federal data (NCES Common Core of Data via the Urban Institute). Returns each school's NCES id, name, district, city, enrollment, charter/magnet status, grade range, and free/reduced-price lunch counts. Use for "public schools in <city/state>", "how many students at ", "charter schools in ", "which schools have the highest enrollment". For school DISTRICTS use education_find_districts; for COLLEGES use the college-scorecard pack instead — this covers K-12 only.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "city": "Austin",
      "state": "TX"
    },
    "name": "education_find_schools"
  }
}

Input Schema

Name	Required	Description
`city`	No	Optional city filter, matched case-insensitively against the school's city.
`year`	No	School year (data year). Default 2020.
`limit`	No	Max schools to return (1-100, default 25).
`state`	Yes	US state name or 2-letter abbreviation, e.g. "Colorado" or "CO". Required.
`charter_only`	No	Return only charter schools.
`name_contains`	No	Optional substring match on the school name, e.g. "Lincoln".

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 6, 2026

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description adds real value beyond that: keyless national data provenance (NCES CCD via Urban Institute) and the enumerable return fields, which tells the agent what it can and cannot extract.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads scope, then data source, then return fields, then routing. Dense but every sentence carries information; the one-sentence return-field list is slightly long but justified given no output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by enumerating returned fields (NCES id, name, district, enrollment, charter/magnet, grade range, lunch counts), and it clarifies data provenance and sibling boundaries. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so every parameter including defaults (year 2020, limit 25) is already documented. The description only restates city/name filtering and charter status at a high level, adding no syntax or format detail beyond the schema — baseline 3 is correct.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb+resource with explicit scope: 'Find US K-12 PUBLIC SCHOOLS by state'. It immediately bounds the domain and distinguishes itself from siblings by naming the district tool and the college pack as out of scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives example query phrasings ('public schools in <city/state>', 'charter schools in <state>') and explicit alternatives: education_find_districts for districts, college-scorecard for colleges, plus 'K-12 only' exclusion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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