University of Maryland College Park
The University of Maryland, College Park (UMD) is the flagship public research university of the University System of Maryland, located in College Park, Maryland, United States. It is ranked #218 in the QS World University Rankings 2025. UMD does not operate a central, officially branded public developer portal. The most prominent public, documented programmatic access to UMD data is umd.io, a student-run open-source REST API (api.umd.io) covering courses, course sections, professors, campus bus routes, building/map data, and majors. The Office of the Registrar's Testudo Schedule of Classes provides course data via a public web interface, and the libraries' DRUM (DSpace) institutional repository is publicly accessible.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles University of Maryland College Park the way a machine reads it — 29 machine-readable artifacts across 7 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — University of Maryland College Park scores 39.8/100 (thin), with a separate agent-readiness read of 39/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile University of Maryland College Park
Each block below is one kind of artifact we hold for University of Maryland College Park. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 7
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Testudo Schedule of Classes
The University of Maryland Office of the Registrar's Testudo Schedule of Classes (SOC) is a public web application for browsing course offerings by semester and department. It i...
DRUM Institutional Repository
DRUM (Digital Repository at the University of Maryland) is the UMD Libraries' DSpace-based institutional repository of scholarship and research outputs. It is publicly browsable...
University of Maryland College Park bus API
This endpoint lets you get data about bus routes, schedules, stops, locations, and predicted arrival times. The data is provided by NextBus, which monitors buses and gives the d...
University of Maryland College Park courses API
This set of endpoints lets you get data about university courses and their sections. You can get one course or section at a time, several courses or sections at a time, or a lis...
University of Maryland College Park majors API
Data about the various majors offered on campus.
University of Maryland College Park map API
Data about things on campus, such as buildings, dining halls, and other facilities.
University of Maryland College Park professors API
This endpoint contains information about university professors and the courses they have taught.
Scroll within the panel for all 7 ·
Pricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
FinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Spectral Rules 2
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
JSON Schema 6
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
JSON Structure 2
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
University Of Maryland College Park Course Structure
JSON STRUCTUREUniversity Of Maryland College Park Section Structure
JSON STRUCTUREExamples 6
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Resources
Every other property we hold for University of Maryland College Park — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/university-of-maryland-college-park · machine-readable index on apis.io