◎ Discry Score
render.com
infrastructure · API
B
0 / 100
DISCOVERY0
COMPREHENSION0
Category leader: 98 (A)
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INFRASTRUCTURE · RANK #15 OF 68

Render is Good to agents.

Discry independently scored how well an AI agent can discover and understand the Render API from what’s public — not whether it’s usable. Below: every signal we checked, what’s costing the score, and what to change.

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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 · 88/100
OpenAPI specA machine-readable OpenAPI/Swagger spec agents can parse.Pass
llms.txtAn llms.txt index that points agents to the docs that matter.Pass
llms.txt qualityThe llms.txt is focused, current, and well under the size budget.Pass
llms-full.txtA full-text bundle agents can load in one request.Pass
AGENTS.mdAn AGENTS.md that tells coding agents how to build on the API.Pass
.well-known/mcp.jsonA discoverable MCP manifest at a well-known path.Fail
MCP registryThe API is listed in a public MCP registry.Pass
robots.txt AI directivesrobots.txt allows (or explicitly guides) AI crawlers.Partial
SitemapA sitemap so agents can enumerate the docs surface.Pass

Comprehension

55% of score · 88/100
Task-oriented descriptionsEndpoints described by what they accomplish, not just their shape.Pass
Realistic examplesRunnable, real-world request/response examples.Partial
Multi-step workflowsDocs that chain calls into complete jobs an agent can follow.Pass
Error-recovery guidanceDocumented failure modes and how to recover from them.Partial
Answer-first formatThe answer leads; preamble does not bury it.Pass
Capability boundariesClear limits — what the API can and cannot do.Pass
Naming consistencyConsistent, predictable naming across endpoints.Pass
Heading hierarchyClean heading structure agents can navigate.Pass
Markdown docsDocs available as clean markdown, not JS-rendered HTML only.Pass
Token efficiencyDocs are concise enough to fit an agent context window.Pass

What we found

  • Render has one of the most thoughtful llms.txt implementations seen: includes metadata, permissions (train: allow, summarize: allow), naming conventions, citation format, and priority guidance for AI agents — a model for the industry
  • The 'Using Render with Coding Agents' dedicated doc page shows explicit investment in agent UX, explaining .md URL appending, Accept header support, and MCP server integration
  • AGENTS.md is present in render-oss repos (skills, cli) and the GitHub org has an official MCP server, Skills repo, and CLI — comprehensive agent tooling ecosystem
  • robots.txt uses Content-Signal to allow search but disallows ai-train and ai-input — a nuanced position that allows agent access but restricts training use
  • llms-full.txt at 825KB provides the entire documentation in a single markdown file with a glossary, link references, and clean structure — exceptional for deep agent comprehension

What to change

Prioritized by impact on discoverability. You (or your docs platform) deploy these — Discry never touches your API.

  1. 01Add .well-known/mcp.json at render.com pointing to the official MCP server at mcp.render.com/mcp — this is the only major discovery signal missing
  2. 02Document API rate limits explicitly — currently not prominently featured in docs, which means agents cannot plan request pacing
  3. 03Replace placeholder values in curl examples (e.g., {{render_api_token_goes_here}}) with realistic-looking masked values to help agents understand expected formats
  4. 04Add dedicated API error recovery documentation showing what to do for common error codes (401, 403, 404, 429, 500) with actionable next steps

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.

api_key Error format documented Rate limits documented Pagination documented Idempotency documented

API key authentication via Bearer token. OpenAPI 3.0 spec available at api-docs.render.com. Interactive API reference with multi-language examples. Rate limit details not prominently documented. Pagination supported for list endpoints.

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