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oliverhruby

EduPage MCP Server

by oliverhruby
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

find_student

Read-onlyIdempotent

Locate a student by first, last, or full name across logged-in EduPage schools, optionally limiting to one subdomain. Returns ranked matches with confidence to avoid ambiguity.

Instructions

Look up a student by first/last/full name using tiered matching. Read-only. Without a subdomain, searches ALL logged-in schools and returns one result per school where the student is found.

Args: name: First, last or full student name (also 'Novák V.' short names). subdomain: Restrict the search to one school (default: all logged-in schools in scope).

Returns: dict with results: [{name, student_id, class_id, subdomain, tier, confidence}] sorted by confidence. Tiers: 1=exact, 2=first name, 3=last name, 4=substring.

Notes: - Use a student_id from the results with get_student_timetable / get_day_summary for unambiguous lookups. - Ambiguous matches surface all candidates instead of guessing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
subdomainNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.6.0
    • addedInput schema / properties / subdomain / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • removedInput schema / properties / subdomain / type
      Removed value: -"string"
  2. First observedv0.4.6

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (which already declare read-only, idempotent, open-world), the description discloses cross-school search scope, the four-tier matching semantics, confidence-based sorting, and the anti-guessing ambiguity policy. This is rich behavioral context an agent cannot infer from structured fields.

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?

Purpose is front-loaded and the Args/Returns/Notes structure is easy to scan. Slightly verbose — 'Read-only' restates the annotation, and the sections add length — but nearly every line carries useful information, so waste is minimal.

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 still documents the return shape (results list with name, student_id, class_id, subdomain, tier, confidence) and tier definitions, plus downstream usage. Nothing needed 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.

Parameters5/5

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

Schema coverage is 0%, so the description carries the full burden, and it does: name accepts first/last/full and short forms like 'Novák V.', and subdomain restricts to one school with default meaning all logged-in schools. Both parameters are fully explained beyond the bare schema types.

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?

States a specific verb (look up), resource (student), and mechanism (tiered matching by first/last/full name). The scope statement about searching ALL logged-in schools without a subdomain further distinguishes it from siblings like get_my_students and scan_students.

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

Usage Guidelines4/5

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

The Notes section tells the agent to reuse a student_id from results with get_student_timetable/get_day_summary for unambiguous lookups, and explains that ambiguous matches surface all candidates. No explicit exclusion against alternative lookup tools, but context is clear.

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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