University of Toronto
The University of Toronto is Canada's largest public research university, operating three campuses (St. George, Mississauga, Scarborough) and ranked in the QS World University Rankings top 25. Like almost every institution its size it is a federation of buyers rather than a producer of APIs, and this profile is deliberate about which side of that line each surface falls on. Two surfaces are genuinely institution-operated, both on utoronto.ca: the Timetable Builder API at api.easi.utoronto.ca, run by Enterprise Applications and Solutions Integration (EASI) within U of T Information Technology Services, which serves live course, section, meeting-time, enrolment and building data across all divisions with no credential required; and the UTORauth Shibboleth identity provider, which publishes SAML 2.0 metadata registered in the Canadian Access Federation with the REFEDS Research & Scholarship entity category and SIRTFI assurance. Everything else that looks like a University of Toronto API is a vendor or consortium contract running under the University's name — TSpace now lives on Scholaris, the OCUL-operated DSpace service, and its OAI-PMH and REST endpoints are the platform's engineering, not U of T's; the U of T Dataverse is a collection inside Borealis. Those relationships are recorded here as tenant surfaces because the data is the University's even though the contract is not. There is no developer portal, no API documentation, no terms of use for any API, no versioning scheme, no status page and no support channel for developers. The University does publish an llms.txt at its web root, which is more agent-facing provision than most of the cohort makes.
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 Toronto the way a machine reads it — 26 machine-readable artifacts across 1 API, 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 Toronto scores 34.5/100 (thin), with a separate agent-readiness read of 23/100 (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. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.
Kin Score
How this is scored →scored 2026-09-08 · rubric v0.20.0
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title="University of Toronto on API Evangelist — API profile and Kin Score">
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</a>More shapes, themes and sizes → · Score as JSON · How badges work
How we profile University of Toronto
Each block below is one kind of artifact we hold for University of Toronto. 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 6
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.
UTORauth Shibboleth Identity Provider (SAML 2.0 metadata)
The University of Toronto's Shibboleth identity provider, entityID https://idpz.utorauth.utoronto.ca/shibboleth, serving signed SAML 2.0 metadata from the University's own utora...
TSpace Institutional Repository (OAI-PMH) — tenant on Scholaris
OAI-PMH 2.0 harvesting endpoint for TSpace, the University of Toronto Libraries institutional research repository. The repository is the University's — Identify returns reposito...
TSpace DSpace REST API — tenant on Scholaris
The DSpace 8.4 HAL REST API serving TSpace. Verified live on 2026-08-19: the root document returns dspaceName "TSpace", dspaceVersion "DSpace 8.4" and a link index covering comm...
U of T Dataverse (Borealis) — tenant
The University of Toronto's research data repository collection inside Borealis, the Canadian Dataverse Repository operated by Scholars Portal for the Ontario Council of Univers...
University of Toronto Courses API
Course, section and meeting-time retrieval.
University of Toronto Reference Data API
Sessions, divisions, campuses and other search facets.
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 things the Kin Score reads for access clarity — renamed from commercial clarity in rubric 0.12, because a free statutory interface has access terms and no commercial ones.
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.
University Of Toronto Rate Limits
RATE LIMITSFinOps 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 2
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 1
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.
University of Toronto API Rules
SPECTRALJSON Schema 4
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.
Examples 7
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.
Ttb Current Session Response
EXAMPLETtb Gateway 404 Response
EXAMPLETtb No Results Response
EXAMPLETtb Pageable Courses Request
EXAMPLETtb Reference Data Response
EXAMPLEScroll within the panel for all 7 ·
Security Posture 2
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.
Scopes 1
OAuth scopes are the vocabulary of least-privilege access. Profiling them shows exactly what an integration — or an agent acting on a user's behalf — is allowed to do.
OAuth scopes governing access to this provider's APIs.
Resources
Every other property we hold for University of Toronto — 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.
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 5
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 3
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
Other 6
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/university-of-toronto · machine-readable index on apis.io
This is an independent, third-party profile of University of Toronto, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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