# Everest

**Canonical:** https://apis.io/providers/everest/  
**Website:** https://www.everestagi.com/  
**APIs profiled:** 0

Everest is an early-stage Y Combinator (Fall 2025 / F25) startup based in San Francisco building agent-ready technical support for developer tools. Its premise is that a growing share of a devtool's users will be coding agents rather than humans, and Everest helps devtool companies sell to and support those coding agents with instant technical support. The company was founded in 2026 by co-founders Yolanda Cao and Spencer McKee. As of this profile Everest operates a single marketing landing page (everestagi.com) with no public API, developer documentation, SDKs, or other developer surface yet published; this record is maintained as a lead for the API Evangelist enrichment pipeline.

## Kin Score — 5.0 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 5.0).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Commercial Clarity | 0.0 |
| Access Clarity | 0.0 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Everest Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Company, Artificial Intelligence, Developer Tools, Technical Support, AI Agents, Coding Agents, Y Combinator, B2B

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/everest/). Scores are computed from the provider's own public artifacts under a published rubric.