SAVA
SAVA (sava.health) is a health-monitoring company developing a minimally invasive, continuous multi-molecule biosensor worn just beneath the skin. The platform is designed to capture real-time molecular data - glucose, lactate, ketones, sodium, histamine, urea, alcohol, and cortisol - and surface it through a connected mobile app, aiming to shift healthcare toward preventative monitoring and personal wellness. The company is early stage and pre-launch, operating a waiting-list model for early access to its device rather than a public product. It publishes no first-party developer API or health-data API; its marketing site is built on Wix and exposes the Wix Site MCP endpoint and a published llms.txt for agentic access to public site content only. Backed by Balderton Capital.
More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.
API Evangelist profiles SAVA the way a machine reads it — 2 machine-readable artifacts, 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 — SAVA scores 18.0/100 (emerging), with a separate agent-readiness read of 12/100 (human only). 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 SAVA
Each block below is one kind of artifact we hold for SAVA. 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.
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
SAVA Site MCP (Wix)
MCP SERVERSecurity Posture 1
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.
Resources
Every other property we hold for SAVA — 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
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Access & Security 1
Authentication, authorization, and security posture
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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