Timber
Timber (timber.io) is the developer-tools company, backed by Lux Capital, that built Vector — an open-source, high-performance observability data pipeline written in Rust. The timber.io domain now redirects to vector.dev, and the project is stewarded by Datadog (which acquired Timber in 2021). Vector collects, transforms, and routes logs, metrics, and traces from many sources through a Vector Remap Language (VRL) transform layer to many sinks, running as a single static binary in agent or aggregator roles. Vector is configuration- driven (YAML/TOML/JSON) rather than an HTTP SaaS; its programmable surface is a local gRPC "Observability API" that lets tooling inspect and interact with a running Vector instance (component topology, metrics, health, live event tapping). This profile enriches the Timber/Vector lead with the real developer surface: the gRPC API, the vector CLI, distribution packages, and project security posture.
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 Timber the way a machine reads it — 5 machine-readable artifacts across 1 API, 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 — Timber scores 27.9/100 (emerging), with a separate agent-readiness read of 25/100 (agent aware). 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 Timber
Each block below is one kind of artifact we hold for Timber. 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 1
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.
Vector Observability API
Vector ships with a local gRPC API that lets you interact with a running Vector instance — inspect component topology, read internal metrics and health, and tap live events flow...
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.
timber-mcp.yml
MCP SERVERSecurity Posture 3
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 Timber — 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 2
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 3
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 4
Pagination, idempotency, versioning, errors, and events
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Operate 3
Status, limits, changes, and where to get help
Company 1
The organization behind the API
Other 2
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/timber · machine-readable index on apis.io