Jupyter Notebook
Jupyter Notebook is the original open-source web application for creating and sharing computational documents that contain live code, equations, visualizations, and narrative text. The Jupyter Notebook server exposes a REST API for managing notebooks, files, kernels, sessions, and terminals, and uses the WebSocket-based Jupyter messaging protocol to communicate with kernels.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles Jupyter Notebook the way a machine reads it — 32 machine-readable artifacts across 14 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 — Jupyter Notebook scores 54.1/100 (developing), with a separate agent-readiness read of 54/100 (agent ready). 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 Jupyter Notebook
Each block below is one kind of artifact we hold for Jupyter Notebook. 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 14
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.
Jupyter Kernel Messaging Protocol
WebSocket-based messaging protocol for communication between Jupyter clients and computational kernels. Supports code execution, introspection, completion, and rich output over ...
Jupyter Notebook Authorization API
Token verification and authorization checks.
Jupyter Notebook Config API
Server configuration section management.
Jupyter Notebook Contents API
File and directory management including notebooks, files, directories, and checkpoints.
Jupyter Notebook General API
General gateway information.
Jupyter Notebook Groups API
Group management for organizing users.
Jupyter Notebook Hub API
Hub lifecycle management.
Jupyter Notebook Kernels API
Kernel lifecycle management on the gateway. The gateway may enforce kernel limits and seed kernels.
Jupyter Notebook Kernelspecs API
Kernel specification listing and retrieval.
Jupyter Notebook Proxy API
Configurable HTTP proxy routing table management.
Jupyter Notebook Services API
The Services API from Jupyter Notebook — 2 operation(s) for services.
Jupyter Notebook Sessions API
Session management for associating notebooks with running kernels.
Jupyter Notebook Terminals API
Terminal session management on the server.
Jupyter Notebook Users API
User management including creation, deletion, server management, and token management.
Scroll within the panel for all 14 ·
Open Collections 3
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Jupyter Notebook Jupyter Kernel Gateway API
OPEN COLLECTIONJupyter Notebook REST API
OPEN COLLECTIONJupyter Notebook JupyterHub REST API
OPEN COLLECTIONPricing 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.
Jupyter Notebook 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.
Jupyter Notebook Finops
FINOPSEvent Specifications 1
Not every API is request/response. AsyncAPI describes the event-driven and streaming side — the webhooks and channels — so the asynchronous half of the interface is documented the same way the synchronous half is.
AsyncAPI definitions for this provider's event-driven and streaming APIs.
Jupyter Kernel Messaging Protocol
The Jupyter Kernel Messaging Protocol defines the WebSocket-based communication between Jupyter clients (notebooks, consoles) and computational kernels. Messages are exchanged o...
ASYNCAPISemantic 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.
Jupyter Notebook Context
JSON-LDSpectral 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.
Jupyter Notebook API Rules
SPECTRALJupyter Notebook 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.
Jupyter Contents Model
JSON SCHEMAJupyter Kernel Message
JSON SCHEMAJupyter Kernel Specification
JSON SCHEMAJupyter Notebook Document
JSON SCHEMASecurity Posture 3
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 Jupyter Notebook — 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.
Get Started 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 3
Status, limits, changes, and where to get help
Company 3
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/jupyter-notebook · machine-readable index on apis.io