NumPy

The fundamental package for scientific computing with Python. NumPy provides multi-dimensional array objects, various derived objects, and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, FFT, and random number generation.

NumPy is listed with 1 API on the APIs.io network. Tagged areas include Data Science, Machine Learning, Numerical Analysis, Open Source, and Python Library.

NumPy’s developer surface includes documentation, changelog, and 6 more developer resources.

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13.4/100 emerging ▬ flat Agent 1/100 human only Front door AI 5/6 prominent Heartbeat 100/100 alive Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

AccessFreemium

1 API

Data Science Machine LearningNumerical AnalysisOpen SourcePython LibraryScientific Computing

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 13.4/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 4.9 / 17

Access Clarity 1.1 / 17

Operational Transparency 2.9 / 11

Contract Governance 0.0 / 10

Discoverability 4.9 / 9

Regulatory Posture 0.0 / 15

Agent readiness — 1/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Education & Research regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document Ask about this →
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship Ask about this →
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author Ask about this →
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey) Ask about this →
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →

12 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points Ask about this →
Access Clarity scores 6.4 — up to +18.7 composite points Ask about this →
Developer Ergonomics scores 28.6 — up to +14.3 composite points Ask about this →

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

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Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/numpy/apis.yml: open an issue on github.com/api-evangelist/numpy to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
Raycast Store Extensions (first-party publishers + community-wrapped products)	covered	26.8 (thin)	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

NumPy API

Core numerical computing library for Python providing multi-dimensional arrays and mathematical functions.

NumPy API pricing

Not yet checked against NumPy's own pricing page. Compiled by API Evangelist on 2026-05-04; confirm before you rely on a figure. A free plan or tier is listed.

Plan	Price
Free freemium	Free
Professional paid	Free
Enterprise enterprise	—

Plan details, limits and sources →

Rate limits

Free Tier Default: 10 requests per minute
Free Tier Monthly Quota: 1000 requests per month
Professional Tier Default: 100 requests per minute

Compiled by API Evangelist, not yet checked against NumPy's documentation. All 5 limits →

Pricing Plans 1

Published pricing tiers and plan structures.

NumPy Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

NumPy Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

NumPy Finops

FINOPS

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

NumPy Domain Security

TLSv1.3 · DMARC

SECURITY

Resources

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 2

Status, limits, changes, and where to get help

RateLimits

RateLimits

ChangeLog

ChangeLog

Commercial 2

Pricing, plans, and the legal terms of use

Plans

Plans

FinOps

FinOps

Company 1

The organization behind the API

Website

Website

Source (apis.yml)

aid: numpy
name: NumPy
description: The fundamental package for scientific computing with Python. NumPy provides multi-dimensional array objects,
  various derived objects, and an assortment of routines for fast operations on arrays, including mathematical, logical, shape
  manipulation, sorting, selecting, I/O, FFT, and random number generation.
type: Index
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: low
  source:
  - plans
  - security
  generated: '2026-11-13'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/numpy.png
x-docs-platform: sphinx
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-10-04
tags:
- Data Science
- Machine Learning
- Numerical Analysis
- Open Source
- Python Library
- Scientific Computing
tags_raw:
- Data Science
- Machine Learning
- Numerical Analysis
- Open Source
- Python Library
- Scientific Computing
- Machine-Learning
- Open-Source
url: https://raw.githubusercontent.com/api-evangelist/numpy/refs/heads/main/apis.yml
created: '2024-01-01'
modified: '2026-04-28'
specificationVersion: '0.23'
apis:
- aid: numpy:numpy-api
  name: NumPy API
  description: Core numerical computing library for Python providing multi-dimensional arrays and mathematical functions.
  humanURL: https://numpy.org/doc/stable/reference/
  tags:
  - Arrays
  - Mathematics
  - Python
  - Scientific Computing
  properties:
  - type: Documentation
    url: https://numpy.org/doc/stable/
  - type: Reference
    url: https://numpy.org/doc/stable/reference/
  - type: GettingStarted
    url: https://numpy.org/doc/stable/user/quickstart.html
common:
- type: Plans
  url: plans/numpy-plans-pricing.yml
- type: RateLimits
  url: rate-limits/numpy-rate-limits.yml
- type: FinOps
  url: finops/numpy-finops.yml
- type: DomainSecurity
  url: security/numpy-domain-security.yml
- type: Website
  url: https://numpy.org/
- type: Documentation
  url: https://numpy.org/doc/stable/
- type: GitHubOrganization
  url: https://github.com/numpy
- type: ChangeLog
  url: https://numpy.org/doc/stable/release.html
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

NumPy API — frequently asked questions

Does NumPy have an API?

Yes. APIs.io lists 1 API from NumPy, including NumPy API.

How much does the NumPy API cost?

APIs.io lists 3 pricing plans for NumPy, with each plan's price, limits and inclusions under Pricing on this page.

Is the NumPy API ready for AI agents?

NumPy has a Kin Score of 13.4 out of 100 (emerging) and an Agent Readiness score of 0.6 (human-only), scored by API Evangelist on 2026-11-13.

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