Stytch is Good to agents.
Discry independently scored how well an AI agent can discover and understand the Stytch 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 · 81/100Comprehension
55% of score · 96/100What we found
- Stytch has the most developer-friendly LLM integration of any API scanned: dedicated 'LLM instructions' page, 'Copy page as Markdown', 'Open in ChatGPT/Claude' on every page, and Documentation Index callout everywhere
- The llms.txt and llms-full.txt files are referenced prominently but require OAuth authentication to access directly — a significant agent-discovery gap since automated agents cannot complete OAuth flows to read documentation
- Stytch has official OpenAPI specs for both the core auth API (stytchauth/stytch-openapi) and the Management API (stytch-management-openapi), plus an official MCP server with OAuth flow built in
- The 'AI agents & apps' and 'Connected Apps' documentation sections show deliberate investment in the agent economy — Stytch is positioning as auth infrastructure for AI agents
- Code examples use realistic values with environment-prefixed IDs (member-test-16d9ba61...) across 6 SDK languages, making them highly copy-pasteable
What to change
Prioritized by impact on discoverability. You (or your docs platform) deploy these — Discry never touches your API.
- 01Make llms.txt publicly accessible without OAuth authentication — gating documentation discovery behind auth defeats the purpose for automated agents
- 02Add .well-known/mcp.json advertising the official Stytch MCP server capabilities
- 03The authentication gate on llms.txt is the single biggest score-limiting factor — removing it would likely push discovery from C to A grade
- 04Consider adding rate limit documentation to public-facing pages (currently may be behind auth)
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.
Basic authentication with project_id and secret. Separate test (test.stytch.com) and live (api.stytch.com) environments. JSON responses. Error codes documented with dedicated Errors section in API reference. Sandbox values for testing. Backend SDKs for Node, Python, Ruby, Go, Java. No idempotency keys mentioned.