Jupyter
Project Jupyter is an open-source initiative that develops the software, open standards, and services for interactive computing across dozens of programming languages. The Jupyter ecosystem includes Jupyter Notebook, JupyterLab, Jupyter Server, JupyterHub, the Jupyter messaging protocol, and supporting client libraries.
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 Jupyter the way a machine reads it — 19 machine-readable artifacts across 12 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 scores 35.6/100 (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 Jupyter
Each block below is one kind of artifact we hold for Jupyter. 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 12
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 Server
Backend that powers Jupyter Notebook, JupyterLab, and other Jupyter web applications. Exposes the core REST API and the WebSocket messaging endpoints used to communicate with ke...
JupyterHub
Multi-user server for Jupyter notebooks. Manages authentication, spawns and proxies multiple instances of the single-user Jupyter notebook server, and exposes a REST API for use...
JupyterLab
Next-generation web-based interactive development environment for notebooks, code, and data, with a JupyterLab Server REST API for settings, workspaces, themes, translations, an...
Jupyter Config API
The Config API from Jupyter — 1 operation(s) for config.
Jupyter Contents API
The Contents API from Jupyter — 3 operation(s) for contents.
Jupyter Jupyter Server REST API API
The Jupyter Server REST API API from Jupyter — 1 operation(s) for jupyter server rest api.
Jupyter Kernels API
The Kernels API from Jupyter — 4 operation(s) for kernels.
Jupyter Kernelspecs API
The Kernelspecs API from Jupyter — 1 operation(s) for kernelspecs.
Jupyter Me API
The Me API from Jupyter — 1 operation(s) for me.
Jupyter Sessions API
The Sessions API from Jupyter — 2 operation(s) for sessions.
Jupyter Status API
The Status API from Jupyter — 1 operation(s) for status.
Jupyter Terminals API
The Terminals API from Jupyter — 2 operation(s) for terminals.
Scroll within the panel for all 12 ·
Open Collections 1
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 Server 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 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 Finops
FINOPSSecurity 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.
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 — 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 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 3
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 2
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 · machine-readable index on apis.io