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Chamber

Chamber is an AIOps control plane for enterprise AI infrastructure (Y Combinator W26, Seattle). Its always-on agent — Chambie — monitors, diagnoses, and automatically resolves GPU workload failures across AWS, GCP, Azure, and on-premise Kubernetes clusters, and optimizes utilization so ML teams can run more workloads on the same GPUs without manual intervention. Chamber ships a REST API, an official Python SDK (chamber-sdk), and a `chamber` CLI for submitting GPU workloads, querying capacity budgets and GPU-hour allocations, and reading GPU utilization / memory / temperature / power metrics, plus Slack and email integrations and Terraform modules for GPU-ready EKS and GKE clusters.

agent ready

Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.

Kin Score

API Evangelist profiles Chamber the way a machine reads it — 7 machine-readable artifacts across 4 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 — Chamber scores 48.8/100 (developing), with a separate agent-readiness read of 51/100 (agent ready). 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 Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 48.8/100 · developing
Contract Quality 15.3 / 25
Developer Ergonomics 16.1 / 20
Commercial Clarity 4.7 / 20
Operational Transparency 2.7 / 13
Governance 0.0 / 12
Discoverability 10.0 / 10
Agent readiness — 51/100 · agent ready
Machine-Readable Contract 18 / 18
Agentic Access Contract 0 / 15
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 8 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 5 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile Chamber

Each block below is one kind of artifact we hold for Chamber. 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 4

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.

Chamber Capacity API

Check budget allocations and remaining GPU hours

Chamber Health API

Service health check

Chamber Metrics API

Query GPU utilization, memory, temperature, and power metrics

Chamber Workloads API

List, retrieve, and get statistics for GPU workloads

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.

chamber-mcp.yml

MCP SERVER

Security 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.

Chamber Authentication

http · 1 scheme

SECURITY

Chamber Domain Security

TLSv1.3 · DNSSEC

SECURITY

Resources

Every other property we hold for Chamber — 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 2

Reference material describing how the API behaves

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

Build 4

SDKs, sample code, and the tooling you integrate with

Access & Security 2

Authentication, authorization, and security posture

Operate 2

Status, limits, changes, and where to get help

Commercial 1

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

← All providers · Data indexed from github.com/api-evangelist/chamber · machine-readable index on apis.io