Zapier is Good to agents.
Discry independently scored how well an AI agent can discover and understand the Zapier API from what’s public — not whether it’s usable. Below: every signal we checked, what’s costing the score, and what to change.
SCORED UNDER RUBRIC 1.2 · A full re-launch under Discry Score 2.5 — a new behavioral instrument, not comparable to these scores — is in progress.
Discovery
45% of score · 67/100Comprehension
55% of score · 96/100What we found
- Zapier has the most agent-intentional documentation of any API scanned: a hierarchical llms.txt system with root map at zapier.com/llms.txt, topic anchors (#mcp, #sdk, #embed), and per-subdomain indexes — purpose-built for agent discovery
- All documentation pages are available as .md URLs (e.g., docs.zapier.com/sdk/quickstart.md), and the quickstart includes 'Open in Codex' deep links for one-click agent setup — a level of agent-native design rarely seen
- The SDK reference is comprehensive (155KB, 126 sections) with TypeScript examples for every method, clear parameter tables, and return type documentation — an agent can immediately start coding without ambiguity
- Despite exceptional documentation quality, Zapier has no public OpenAPI spec for its own API — ironic for a platform that helps other APIs integrate, and it costs 5 points in discovery scoring
- AGENTS.md exists in the zapier/sdk repo with explicit rules for coding agents: 'no hallucinating method names; use listActions / getActionInputFieldsSchema to discover capabilities at runtime'
What to change
Prioritized by impact on discoverability. You (or your docs platform) deploy these — Discry never touches your API.
- 01Publish an OpenAPI spec for the Zapier SDK/API — this is the single biggest discovery gap (weight: 5) and ironic for an API integration platform
- 02Add .well-known/mcp.json at zapier.com pointing to the official Zapier MCP server for standardized machine discovery
- 03Add llms-full.txt combining the SDK reference, MCP docs, and integration builder docs into a single comprehensive markdown file
- 04Add more explicit error recovery guidance in the SDK reference — currently error handling patterns are sparse compared to the exceptional quality of everything else
Execution coverage · INFORMATIONAL, UNSCORED
Whether an agent can actually complete a call and recover from errors is the deeper Audit layer — documented here, but not part of the Discry Score.
TypeScript SDK with multiple auth options (browser-based, client credentials, direct token). JSON responses with error details. Usage limits and billing documented for MCP and SDK. Cursor-based pagination via SDK methods. No idempotency documentation found.