CoTeach

CoTeach is an AI-powered curriculum co-planning assistant for K-12 mathematics teachers, built by Teaching Lab and deeply integrated with the Illustrative Mathematics (IM v.360) curriculum. Through a chat interface, teachers adapt lessons, generate curriculum-aligned practice problems and worksheets, build scaffolds and differentiated supports for multilingual learners and students with IEPs, and produce IM-style math diagrams (number lines, tape diagrams, area models), exporting to PDF or Google Docs. CoTeach preserves IM's pedagogical framework, collects no student data, and meters usage by message credits. It also exposes a hosted, OAuth-protected Model Context Protocol (MCP) server (the "Coteach Claude connector") and publishes an llms.txt so AI agents can discover the product and hand off to it.

CoTeach is profiled on the APIs.io network. Tagged areas include Company, Education, EdTech, Mathematics, and K-12.

CoTeach’s developer surface includes pricing, engineering blog, support, authentication, and 12 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

22.5/100 emerging ▬ flat Agent 27/100 agent aware Front door AI 4/6 moderate Heartbeat 100/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

0 APIs 1 MCP Servers

Company Education EdTech Mathematics K-12 Teachers CurriculumLesson PlanningAI AssistantIllustrative MathematicsMCP

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 22.5/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 3.2 / 17

Access Clarity 6.5 / 17

Operational Transparency 0.6 / 11

Contract Governance 1.9 / 10

Discoverability 5.0 / 9

Regulatory Posture 5.1 / 15

Agent readiness — 27/100 · agent aware

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 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 6 / 6

Protected Resource Metadata 5 / 5

Registration Without a Human 6 / 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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<a href="https://apis.io/providers/coteach/"><img src="https://apis.io/badge/coteach/card.svg" alt="CoTeach on APIs.io — Kin Score by API Evangelist"></a>

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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
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
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)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Rate-Limit Signaling +7 pts — OpenAPI responses document X-RateLimit-* / RateLimit headers (verified), else a rate_limits artifact or RateLimits link (documented)

8 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
Developer Ergonomics scores 19.0 — up to +16.2 composite points
Access Clarity scores 38.2 — up to +12.4 composite points

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.

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/coteach/apis.yml: open an issue on github.com/api-evangelist/coteach 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 →

Standards implemented 3

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

Model Context Protocol (MCP)

measured — observed by APIs.io (verified)

OAuth 2.0 Protected Resource Metadata

measured — observed by APIs.io (verified)

Dynamic Client Registration

measured — observed by APIs.io (published)

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Coteach Claude connector

Remote MCP server at www.coteach.ai over HTTP.

MCP SERVER

Security Posture 2

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

Coteach Authentication

oauth2/openIdConnect · 2 schemes

SECURITY

Coteach Domain Security

TLSv1.3 · HSTS

SECURITY

Scopes 1

OAuth scopes governing access to this provider's APIs.

Coteach Scopes

4 scopes · authorizationCode

4 scopes

SCOPES

Resources

Get Started 1

Portal, sign-up, and the first successful call

Login

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

WellKnown

WellKnown

MCPServer

MCPServer

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Access & Security 3

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

OAuthScopes

OAuthScopes

Operate 2

Status, limits, changes, and where to get help

Support

Support

Roadmap

Roadmap

Commercial 3

Pricing, plans, and the legal terms of use

Pricing

Pricing

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 3

The organization behind the API

BlogRSS

BlogRSS

Website

Website

Blog

Blog

Source (apis.yml)

aid: coteach
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - scopes
  - security
  generated: '2026-11-06'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/coteach.png
name: CoTeach
description: CoTeach is an AI-powered curriculum co-planning assistant for K-12 mathematics teachers, built by Teaching Lab
  and deeply integrated with the Illustrative Mathematics (IM v.360) curriculum. Through a chat interface, teachers adapt
  lessons, generate curriculum-aligned practice problems and worksheets, build scaffolds and differentiated supports for multilingual
  learners and students with IEPs, and produce IM-style math diagrams (number lines, tape diagrams, area models), exporting
  to PDF or Google Docs. CoTeach preserves IM's pedagogical framework, collects no student data, and meters usage by message
  credits. It also exposes a hosted, OAuth-protected Model Context Protocol (MCP) server (the "Coteach Claude connector")
  and publishes an llms.txt so AI agents can discover the product and hand off to it.
url: https://raw.githubusercontent.com/api-evangelist/coteach/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- 500-global
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
tags:
- Company
- Education
- EdTech
- Mathematics
- K-12
- Teachers
- Curriculum
- Lesson Planning
- AI Assistant
- Illustrative Mathematics
- MCP
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- url: https://coteach.ai/blog/rss.xml
  type: BlogRSS
- type: DomainSecurity
  url: security/coteach-domain-security.yml
- type: Website
  url: https://www.coteach.ai
- type: Pricing
  url: https://www.coteach.ai/pricing
- type: Login
  url: https://www.coteach.ai/chat?login=true
- type: TermsOfService
  url: https://www.coteach.ai/terms
- type: PrivacyPolicy
  url: https://www.coteach.ai/privacy
- type: Blog
  url: https://www.coteach.ai/blog
- type: Support
  url: https://www.coteach.ai/faqs
- type: Roadmap
  url: https://coteach.feedbear.com/roadmap
- type: LLMsTxt
  url: llms/coteach-llms.txt
- type: WellKnown
  url: well-known/coteach-well-known.yml
- type: MCPServer
  url: mcp/coteach-mcp.yml
- type: Authentication
  url: authentication/coteach-authentication.yml
- type: OAuthScopes
  url: scopes/coteach-scopes.yml
- type: Conformance
  url: conformance/coteach-conformance.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

CoTeach API — frequently asked questions

How do I authenticate with the CoTeach API?

CoTeach documents its authentication (oauth2/openIdConnect · 2 schemes). The details are profiled on APIs.io as Coteach Authentication.

Does CoTeach have an MCP server?

Yes. APIs.io lists 1 MCP server for CoTeach: Remote MCP server at www.coteach.ai over HTTP.

Is the CoTeach API ready for AI agents?

CoTeach has a Kin Score of 22.5 out of 100 (emerging) and an Agent Readiness score of 27.3 (agent-aware), scored by API Evangelist on 2026-11-06.

Work with this as data

Every provider here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for providers

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get_provider_artifactsEvery artifact this provider publishes, grouped by type.
get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
find_cohortsEvery scored population of providers in the catalog.

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Every operation they expose

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How their score was established

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