Hyperprobe

Hyperprobe is a runtime data platform for AI-native software development, built by a San Francisco team in Y Combinator's Summer 2026 batch. It lets developers and coding agents (Cursor, Claude Code, Codex, opencode, Windsurf) set live, non-breaking breakpoints in running production services directly from the IDE — capturing exact variable snapshots, injecting logs, and tracing call stacks without pausing threads, redeploying, or changing source code. Probes are read-only and non-blocking with under 1% overhead, and PII is redacted in-process before any data leaves the container's memory boundary (password, secret, token, authorization, cookie, key, signature, ssn and creditCard patterns are masked by default). Hyperprobe ships in-process SDKs for Node.js (@hyperprobe/node-sdk), Java (a bytecode-instrumentation agent), and Python (hyperprobe-agent), a VS Code extension, and an official Model Context Protocol (MCP) server (@hyperprobe/mcp-server) that lets AI assistants autonomously register conditional probes and read real runtime evidence instead of flat logs. The platform can run fully self-hosted via Docker Compose. Originally added to the API Evangelist network as a Y Combinator portfolio lead, this profile has been enriched from Hyperprobe's public developer surface.

Hyperprobe is profiled on the APIs.io network. Tagged areas include Company, Observability, Debugging, Developer Tools, and Runtime.

Hyperprobe’s developer surface includes documentation, getting-started guide, signup flow, CLI, and 9 more developer resources.

🌐 Visit website 📡 Source on GitHub

19.6/100 emerging ▬ flat Agent 0/100 human only saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

0 APIs 1 MCP Servers

Company Observability Debugging Developer Tools Runtime Artificial Intelligence MCP SDKProduction Debugging

Kin Score

Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0

Composite quality — 19.6/100 · emerging

Contract Quality 0.0 / 25

Developer Ergonomics 9.0 / 20

Access Clarity 2.6 / 20

Operational Transparency 0.0 / 13

Contract Governance 2.2 / 12

Discoverability 5.7 / 10

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 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 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/hyperprobe: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

MCP Servers 1

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

Hyperprobe MCP Server

Official Hyperprobe MCP server, published to npm as @hyperprobe/mcp-server and run locally over stdio. It lets AI coding agents autonomously debug and trace running production c...

MCP SERVER

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Hyperprobe Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 3

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

SignUp

SignUp

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

LLMsTxt

LLMsTxt

WellKnown

WellKnown

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Build 3

SDKs, sample code, and the tooling you integrate with

SDKs

SDKs

Packages

Packages

CLI

CLI

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Company 1

The organization behind the API

Website

Website

Source (apis.yml)

aid: hyperprobe
name: Hyperprobe
description: Hyperprobe is a runtime data platform for AI-native software development, built by a San Francisco team in Y
  Combinator's Summer 2026 batch. It lets developers and coding agents (Cursor, Claude Code, Codex, opencode, Windsurf) set
  live, non-breaking breakpoints in running production services directly from the IDE — capturing exact variable snapshots,
  injecting logs, and tracing call stacks without pausing threads, redeploying, or changing source code. Probes are read-only
  and non-blocking with under 1% overhead, and PII is redacted in-process before any data leaves the container's memory boundary
  (password, secret, token, authorization, cookie, key, signature, ssn and creditCard patterns are masked by default). Hyperprobe
  ships in-process SDKs for Node.js (@hyperprobe/node-sdk), Java (a bytecode-instrumentation agent), and Python (hyperprobe-agent),
  a VS Code extension, and an official Model Context Protocol (MCP) server (@hyperprobe/mcp-server) that lets AI assistants
  autonomously register conditional probes and read real runtime evidence instead of flat logs. The platform can run fully
  self-hosted via Docker Compose. Originally added to the API Evangelist network as a Y Combinator portfolio lead, this profile
  has been enriched from Hyperprobe's public developer surface.
url: https://raw.githubusercontent.com/api-evangelist/hyperprobe/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- y-combinator
x-tier: stub
x-tier-reason: portfolio-lead
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-19'
image: https://hyperprobe.co/favicon.svg
tags:
- Company
- Observability
- Debugging
- Developer Tools
- Runtime
- Artificial Intelligence
- MCP
- SDK
- Production Debugging
tags_raw:
- Company
- Observability
- Debugging
- Developer Tools
- Runtime
- AI
- MCP
- SDK
- Production Debugging
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://hyperprobe.co/
- type: DeveloperPortal
  url: https://docs.hyperprobe.co/
- type: Documentation
  url: https://docs.hyperprobe.co/
- type: GettingStarted
  url: https://docs.hyperprobe.co/quickstart
- type: SignUp
  url: https://app.hyperprobe.co
- type: SDKs
  url: packages/hyperprobe-packages.yml
- type: Packages
  url: packages/hyperprobe-packages.yml
- type: MCPServer
  url: mcp/hyperprobe-mcp.yml
- type: CLI
  url: cli/hyperprobe-cli.yml
- type: LLMsTxt
  url: llms/hyperprobe-llms.txt
- type: WellKnown
  url: well-known/hyperprobe-well-known.yml
- type: Conformance
  url: conformance/hyperprobe-conformance.yml
- type: DomainSecurity
  url: security/hyperprobe-domain-security.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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