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Rerun

Rerun is an open-source data platform — "the unified data layer for physical AI" — for multimodal, multi-rate time-series data from robotics and computer vision. It provides the data primitives to log, store, query, transform, and visualize images, point clouds, tensors, transforms, and other sensor streams from initial recording through production scale. The open-source toolchain (a logging SDK across Python, Rust, and C++, an interactive desktop/web viewer, SQL/dataframe queries, a PyTorch dataloader, the columnar .rrd file format, and a local catalog) is free and dual-licensed MIT OR Apache-2.0; Rerun Hub is the commercial managed backend adding a persistent catalog, byte-range indexing across object stores, dataset streaming to GPUs, SSO, and single-tenant deployment. Rerun's programmatic surface is an SDK plus a gRPC data server and a Viewer MCP server, rather than a hosted REST API. Backed by Costanoa Ventures, Point Nine, and Seedcamp.

agent aware

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.

Kin Score

API Evangelist profiles Rerun 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 — Rerun scores 25.1/100 (emerging), with a separate agent-readiness read of 15/100 (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 Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 25.1/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 10.9 / 20
Commercial Clarity 4.7 / 20
Operational Transparency 2.7 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Agent readiness — 15/100 · agent aware
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
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 4 / 4
Consent & Bot Identity 0 / 3

How we profile Rerun

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

rerun-mcp.yml

MCP SERVER

Security 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.

Rerun Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Every other property we hold for Rerun — 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 3

Pagination, idempotency, versioning, errors, and events

Build 4

SDKs, sample code, and the tooling you integrate with

Access & Security 1

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/rerun · machine-readable index on apis.io