Gangkhar

Gangkhar is an AI-native embedded protection infrastructure platform that lets digital platforms, insurers, MGAs, and brokers configure, launch, and continuously optimize embedded insurance products globally through a single infrastructure layer and API. Its Sherpa+ engine provides full-stack embedded protection rails covering onboarding, pricing, underwriting, and claims across multiple carriers and markets, while Sherpa+Lens applies real-time AI optimization to pricing, messaging, and product versions. The platform enables sectors like mobility, delivery, fintech, e-commerce, travel, health, and vertical SaaS to embed compliant protection directly into their customer experiences without becoming insurers themselves. Founded in 2025 and led by former Chubb executive Federico Spagnoli, Gangkhar closed a $4.25M seed round in March 2026 led by Anthemis. Surfaced as an Anthemis portfolio company and enriched into the API Evangelist network.

Gangkhar is profiled on the APIs.io network. Tagged areas include Company, Insurance, Embedded Insurance, Insurtech, and Embedded Finance.

Gangkhar’s developer surface includes FAQ, support, engineering blog, YouTube channel, and 8 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

7.8/100 minimal ▬ flat Agent 2/100 human only Front door AI 5/6 prominent Heartbeat 79/100 alive Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

0 APIs 1 MCP Servers

Company Insurance Embedded Insurance Insurtech Embedded Finance Protection Artificial Intelligence Fintech Underwriting Claims

Kin Score

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

Composite quality — 7.8/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 1.2 / 17

Access Clarity 1.8 / 17

Operational Transparency 0.0 / 11

Contract Governance 0.0 / 10

Discoverability 4.7 / 9

Regulatory Posture 1.2 / 15

Agent readiness — 2/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 0 / 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 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 Insurance 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
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
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)
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

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
Developer Ergonomics scores 7.1 — up to +18.6 composite points
Access Clarity scores 10.5 — up to +17.9 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/gangkhar/apis.yml: open an issue on github.com/api-evangelist/gangkhar 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 2

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 (platform)

Universal Commerce Protocol (UCP)

measured — observed by APIs.io (wix)

MCP Servers 1

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

Gangkhar Site MCP

Gangkhar's public website (gangkhar.com) is powered by Wix and advertises a hosted, remote Model Context Protocol (MCP) endpoint in its llms.txt for agentic AI access to live, p...

MCP SERVER

Security Posture 1

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

Gangkhar Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

MCPServer

MCPServer

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Learn 1

Tutorials, courses, talks, and written guidance

YouTube

YouTube

Operate 2

Status, limits, changes, and where to get help

FAQ

FAQ

Support

Support

Commercial 1

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

Company 5

The organization behind the API

BlogRSS

Website

About

Blog

LinkedIn

Source (apis.yml)

aid: gangkhar
name: Gangkhar
description: Gangkhar is an AI-native embedded protection infrastructure platform that lets digital platforms, insurers, MGAs,
  and brokers configure, launch, and continuously optimize embedded insurance products globally through a single infrastructure
  layer and API. Its Sherpa+ engine provides full-stack embedded protection rails covering onboarding, pricing, underwriting,
  and claims across multiple carriers and markets, while Sherpa+Lens applies real-time AI optimization to pricing, messaging,
  and product versions. The platform enables sectors like mobility, delivery, fintech, e-commerce, travel, health, and vertical
  SaaS to embed compliant protection directly into their customer experiences without becoming insurers themselves. Founded
  in 2025 and led by former Chubb executive Federico Spagnoli, Gangkhar closed a $4.25M seed round in March 2026 led by Anthemis.
  Surfaced as an Anthemis portfolio company and enriched into the API Evangelist network.
url: https://raw.githubusercontent.com/api-evangelist/gangkhar/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- anthemis
x-tier: stub
x-tier-reason: portfolio-lead
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: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - security
  generated: '2026-11-06'
  method: derived
image: https://static.wixstatic.com/media/84a20e_d1dafb944cb5498bb07972a03101b8cb~mv2.png/v1/fit/w_2500,h_1330,al_c/84a20e_d1dafb944cb5498bb07972a03101b8cb~mv2.png
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
tags:
- Company
- Insurance
- Embedded Insurance
- Insurtech
- Embedded Finance
- Protection
- Artificial Intelligence
- Fintech
- Underwriting
- Claims
tags_raw:
- Company
- Insurance
- Embedded Insurance
- InsurTech
- Embedded Finance
- Protection
- AI
- Fintech
- Underwriting
- Claims
apis: []
common:
- url: https://www.gangkhar.com/blog-feed.xml
  type: BlogRSS
- type: Website
  url: https://www.gangkhar.com/
- type: About
  url: https://www.gangkhar.com/about-us
- type: FAQ
  url: https://www.gangkhar.com/faq
- type: Support
  url: https://www.gangkhar.com/contact-us
- type: Blog
  url: https://www.gangkhar.com/press-blog
- type: PrivacyPolicy
  url: https://www.gangkhar.com/privacy-policy
- type: LinkedIn
  url: https://www.linkedin.com/company/gangkhar
- type: YouTube
  url: https://www.youtube.com/@GangkharGlobal
- type: LLMsTxt
  url: llms/gangkhar-llms.txt
- type: MCPServer
  url: mcp/gangkhar-mcp.yml
- type: DomainSecurity
  url: security/gangkhar-domain-security.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

Gangkhar API — frequently asked questions

Does Gangkhar have an MCP server?

Yes. APIs.io lists 1 MCP server for Gangkhar: Gangkhar's public website (gangkhar.com) is powered by Wix and advertises a hosted, remote Model Context Protocol (MCP) endpoint in its llms.txt for agentic AI access to live, public site content. Thi

Is the Gangkhar API ready for AI agents?

Gangkhar has a Kin Score of 7.8 out of 100 (minimal) and an Agent Readiness score of 2.2 (human-only), scored by API Evangelist on 2026-11-06.

Work with this as data

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MCP server

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

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Tools for providers

9 MCP tools reach this

find_providersBrowse and filter every provider in the catalog.
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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