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.

Rerun is profiled on the APIs.io network. Tagged areas include Company, Dev Tools Ai, Robotics, Computer Vision, and Physical AI.

Rerun’s developer surface includes documentation, API reference, getting-started guide, engineering blog, pricing, signup flow, support, and 13 more developer resources.

🌐 Visit website 📡 Source on GitHub

25.1/100 emerging ▬ flat Agent 15/100 agent aware Full breakdown ↓
scored 2026-07-27 · rubric v0.5

0 APIs 1 MCP Servers

CompanyDev Tools AiRoboticsComputer VisionPhysical AIData VisualizationSDKOpen SourceMCP

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

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/rerun: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

MCP Servers 1

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

Get Started 2

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

SignUp

SignUp

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

WellKnown

WellKnown

LLMsTxt

LLMsTxt

Design & Contract 3

Pagination, idempotency, versioning, errors, and events

Components

Components

Lifecycle

Lifecycle

Conformance

Conformance

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 2

Status, limits, changes, and where to get help

Support

Support

ChangeLog

ChangeLog

Commercial 1

Pricing, plans, and the legal terms of use

Pricing

Pricing

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: rerun
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/rerun.png
name: Rerun
description: 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.
url: https://raw.githubusercontent.com/api-evangelist/rerun/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- costanoa-ventures
- point-nine
- seedcamp
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Dev Tools Ai
- Robotics
- Computer Vision
- Physical AI
- Data Visualization
- SDK
- Open Source
- MCP
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://rerun.io
- type: Documentation
  url: https://rerun.io/docs/overview/what-is-rerun
- type: APIReference
  url: https://rerun.io/docs/reference/types/archetypes
- type: GettingStarted
  url: https://rerun.io/docs/getting-started/quick-start
- type: Blog
  url: https://rerun.io/blog
- type: Pricing
  url: https://rerun.io/pricing
- type: GitHubOrganization
  url: https://github.com/rerun-io
- type: SignUp
  url: https://rerun.io/pricing
- type: Support
  url: https://discord.gg/PXtCgFBSmH
- type: Packages
  url: packages/rerun-packages.yml
- type: SDKs
  url: packages/rerun-packages.yml
- type: CLI
  url: cli/rerun-cli.yml
- type: Components
  url: components/rerun-components.yml
- type: MCPServer
  url: mcp/rerun-mcp.yml
- type: ChangeLog
  url: changelog/rerun-changelog.yml
- type: Lifecycle
  url: lifecycle/rerun-lifecycle.yml
- type: Conformance
  url: conformance/rerun-conformance.yml
- type: WellKnown
  url: well-known/rerun-well-known.yml
- type: DomainSecurity
  url: security/rerun-domain-security.yml
- type: LLMsTxt
  url: llms/rerun-llms.txt
x-enrichment:
  date: '2026-07-20'
  status: enriched
  artifacts_added: 10
  pass: local-v1