Agent MCP Directory

Docker: the 360 agent-readiness check

Docker scores 69 of 100 on Ora's agent-readiness scan, a C, read 9 November 2026. Of the five surfaces an agent acts on, Ora found 3: an MCP server, OAuth, a command line. A live MCP handshake and six agents through the door, with no API description.

On 9 November 2026 the public site at docker.com scored 69 of 100 on Ora's agent-readiness scan, a C, in Ora's Infrastructure category. Ora probes a site the way an agent would: it requests pages with the agents' own user agents, reads robots.txt, looks for the files agents read, and tries the API, MCP and payment surfaces. This check reads the act layer first, because that is what the directory records, then the door, what an agent can read, and whether the company is found and recommended. Ora's one-line summary: Docker offers developer resource discoverability, but lacks an OpenAPI specification.

The score

Docker on Ora, read 2026-11-09: points per layer, with the share of each layer's maximum. 40 checks pass, 11 are partial, 38 fail and 42 do not apply to this site.
LayerAsksPointsShare
UsabilityCan agents use it43 of 7161%
AccessCan agents read it42 of 6268%
DiscoveryCan agents find and recommend it13 of 1587%
PaymentsCan agents pay0 of 0none apply
TotalGrade C69 of 10069%

What an agent can do

The surfaces an agent acts on: an API it can find and call, an MCP server, an agent card, OAuth metadata, a command line. This is the layer the directory records, so it comes first. 2 checks in this group do not apply to this site and are left out.

In the directory, Docker not counted (no answer); the connector run of 4 November 2026 is on the entry page. Ora's MCP server check for the same domain reads pass; the two look for different things, the directory for a server that answers a handshake and lists tools, Ora for a server it can find from the site.

What an agent can do: 17 checks Ora ran on docker.com, read 2026-11-09. The last column is Ora's own observation where it published one.
CheckResultPointsWhat Ora saw
MCP server / manifest mcp-serverPass6 of 6MCP server connected via Streamable HTTP - llms-txt v1.26.0 (protocol 2025-11-25)
MCP well-known discovery mcp-well-known-discoveryPass2 of 2MCP server referenced in llms.txt
Public API with reachable endpoints public-apiPartial3 of 7API described in documentation at https://docs.docker.com but no machine-verifiable API surface confirmed. Best-of-protocols score: 3/7.
Public API/docs linked from homepage public-api-docsPass3 of 3Documentation site found at https://docs.docker.com
Developer portal developer-portalPass6 of 6Developer portal found at /developers
OpenAPI spec published openapi-specFail0 of 7No OpenAPI/Swagger specification found
API catalog (RFC 9727) api-catalog-rfc9727Fail0 of 2No /.well-known/api-catalog found (RFC 9727)
A2A / agent-card a2a-agent-cardFail0 of 2No A2A agent card found at /.well-known/agent-card.json
Agent discovery file agent-discovery-fileFail0 of 2No agent discovery file found
OAuth 2.0 support oauth-supportPass5 of 5OpenID Connect discovery endpoint found at https://login.docker.com
OAuth Protected Resource metadata (RFC 9728) oauth-protected-resourceFail0 of 2No /.well-known/oauth-protected-resource found (RFC 9728)
auth.md exists auth-md-existsFail0 of 2No /auth.md found at site root
WebMCP support webmcpFail0 of 5No WebMCP support detected - no tool-attribute forms and no document.modelContext / navigator.modelContext usage found (scanned 8 of 43 same-origin script bundle(s) for modelContext registrations)
NLWeb /ask endpoint nlweb-askFail0 of 1No NLWeb-conformant /ask endpoint found via GET or POST
CLI tool available cli-toolPass3 of 3CLI package found on npm: docker
Multi-language SDK packages rest-sdk-packagesPartial2 of 3SDK packages found in npm, pypi
JSON error responses json-error-responsesFail0 of 4API does not return JSON error responses (or no API detected)

At the door

What the site answers when a request arrives with an agent's user agent, and what robots.txt says to agents.

At the door: 7 checks Ora ran on docker.com, read 2026-11-09. The last column is Ora's own observation where it published one.
CheckResultPointsWhat Ora saw
Not blocked by bot detection bot-detectionPass2 of 2Site accessible to 6 AI agent user-agents
Agent crawler reachability agent-crawler-reachabilityPass2 of 2Reachable to all major AI crawlers - ChatGPT-User: reachable, ClaudeBot: reachable, Google-Extended: reachable, ora-agent: reachable, DeepSeekBot: reachable
robots.txt AI crawler policy robots-ai-policy-qualityPass2 of 2Training: 2/2. Search: 3/3 page/crawler pairs permitted. No applicable crawl or usage restriction found for 5 training and search crawlers (gptbot, claudebot, oai-searchbot, claude-searchbot,
robots.txt agent-user policy robots-agent-user-policyPass2 of 2No applicable crawl or usage restriction found for 3 user-triggered agents (chatgpt-user, claude-user, perplexity-user) on 1 public page: https://docker.com/. Declared policy only;
Content behind auth docs-auth-gatePass2 of 2All 5 sampled pages are publicly readable (5 with substantive content)
Redirect hygiene redirect-hygienePass1 of 1no detail published
Web Bot Auth directory web-bot-auth-directoryFail0 of 2No /.well-known/http-message-signatures-directory found

What an agent can read

Whether the text is in the first response, what the site publishes for agents, and how it describes itself to them.

What an agent can read: 17 checks Ora ran on docker.com, read 2026-11-09. The last column is Ora's own observation where it published one.
CheckResultPointsWhat Ora saw
Content without JavaScript content-no-jsPartial2 of 34009 chars with H1, but heading hierarchy skips H1 to H4; 4.2% content ratio is below the 5% target
Page token budget page-token-budgetPass1 of 1All 6 measured pages fit an agent context budget (largest ~3K tokens)
Sitemap exists sitemapPass2 of 2Valid sitemap found at https://www.docker.com/sitemap_index.xml with multiple sitemaps entries
Sitemap freshness (lastmod) sitemap-lastmodPass1 of 1no detail published
llms.txt exists llms-txt-existsPass1 of 1Found the llms.txt at https://docs.docker.com/llms.txt.
llms.txt formatting llms-txt-formattingPass2 of 2The llms.txt is well-formatted: 59 lines with markdown links, 5,584 characters in total.
llms.txt links resolve llms-txt-links-resolvePass2 of 2no detail published
Markdown agent docs markdown-negotiationFail0 of 1Missing markdown content negotiation. Homepage returned text/html when probed with Accept: text/markdown (expected text/markdown), and none of the well-known root paths (/llms.md, /auth.md, /agents.md, /developers.md,
Markdown URL fallback markdown-url-fallbackFail0 of 2Homepage does not support the .md suffix. Probed https://docker.com/index.md and it did not return markdown (expected text/markdown content-type or a heading-led non-HTML body).
Bot-UA markdown serving agent-ua-markdownFail0 of 1No probed bot User-Agent (GPTBot, ClaudeBot, ChatGPT-User, PerplexityBot, Google-Extended, Applebot-Extended, ora-agent, DeepSeekBot) receives markdown when requesting HTML.
Agent mode view agent-mode-viewFail0 of 2?mode=agent returns same content as homepage (no dedicated agent view)
JSON-LD structured data json-ldPartial1 of 4JSON-LD found (1 block(s)) but no identity type - use SoftwareApplication, Product, Organization, Person, or Article so agents can tell what this site is
Organization schema completeness org-schema-completenessFail0 of 2No Organization type found in JSON-LD
JSON-LD entity linking (sameAs) json-ld-entity-linkingPass2 of 2no detail published
Schema type breadth schema-type-breadthFail0 of 2No extended schema types found - AI can only answer basic questions about this entity
Metadata completeness metadata-completenessPass2 of 2All metadata signals present: canonical URL, lang="en-US", og:image, og:type
Agent instruction / when-to-use agent-instructionFail0 of 3No agent instruction file with when-to-use guidance found

Found and recommended

Whether an assistant can find the company by name, confirm what it is, and see it in the registries agents read.

Found and recommended: 9 checks Ora ran on docker.com, read 2026-11-09. The last column is Ora's own observation where it published one.
CheckResultPointsWhat Ora saw
Brand name discoverability brand-search-accuracyPass3 of 3docker.com ranks #1 for "Docker AI agent platform"
Wikipedia / Wikidata entity presence wikipedia-presencePass4 of 4Wikipedia "Docker (software)" and Wikidata Q15206305 both verified - domain confirmed on both sources
Developer resource discoverability agentic-search-specificPass3 of 3no detail published
Listed in MCP registries mcp-registry-listedFail0 of 1No bi-directionally verified MCP registry entry found. To pass, either publish the server from a package whose homepage, repository or maintainer email names your domain, get a verified Smithery listing with non-zero usage,
NPM/PyPI SDK package npm-sdk-packagePass1 of 1no detail published
ChatGPT app listed chatgpt-app-listedFail0 of 2Not found in ChatGPT app directory
Registry branding registry-brandingFail0 of 2No registry branding (name, icon, description) found
Listed on skills.sh skills-sh-listedPass1 of 1no detail published
ARD discovery ard-catalogFail0 of 1No /.well-known/ard.json (and no legacy /.well-known/ai-catalog.json)

Payments

The agent payment protocols Ora probes for. A site that sells nothing has nothing here, and Ora scores the layer out of zero when none applies. 5 checks in this group do not apply to this site and are left out.

Payments: 1 checks Ora ran on docker.com, read 2026-11-09. The last column is Ora's own observation where it published one.
CheckResultPointsWhat Ora saw
MPP payment protocol mpp-supportPartial0 of 2MPP documented (AI analysis: MCP endpoint for structured agent access: https://mcp-docs.docker.com/mcp); no live protocol surface found

The fixes worth most points

Ora attaches an estimate to each failing or partial check: how many points the site would gain by passing it. These are the 5 with the largest estimates for Docker, with what Ora observed. The wording of each fix is Ora's; the 28 checks it runs on an MCP server are listed with their layer and tier.

  • OpenAPI spec published: fail, 0 of 7, about 3.8 points to gain. Ora saw: No OpenAPI/Swagger specification found
  • Scoped permissions: fail, 0 of 5, about 3.1 points to gain. Ora saw: No declared OAuth scopes, security schemes, or scoped-permission documentation found
  • WebMCP support: fail, 0 of 5, about 3.1 points to gain. Ora saw: No WebMCP support detected - no tool-attribute forms and no document.modelContext / navigator.modelContext usage found (scanned 8 of 43 same-origin script bundle(s) for modelContext registrations)
  • JSON error responses: fail, 0 of 4, about 2.5 points to gain. Ora saw: API does not return JSON error responses (or no API detected)
  • Public API with reachable endpoints: partial, 3 of 7, about 2.5 points to gain. Ora saw: API described in documentation at https://docs.docker.com but no machine-verifiable API surface confirmed. Best-of-protocols score: 3/7.

Our read

Docker's MCP server completed a live handshake with Ora, llms-txt version 1.26.0 over Streamable HTTP on protocol 2025-11-25, and the door is open to all six agent user agents Ora sent. The rest of the act layer is lighter than that start suggests: the API is described at docs.docker.com with no machine-verifiable surface, there is no OpenAPI specification, no declared scopes, and the endpoints Ora tried do not answer errors as JSON; OpenID Connect discovery at login.docker.com, the docker package on npm and SDKs in npm and PyPI are what counts. The reading side holds it to a C as well, with a JSON-LD block that has no identity type, a heading tree that skips from H1 to H4 and a text ratio just under 5 percent, though docs.docker.com carries an llms.txt and the domain ranks first for its agent platform term. A live server with nothing describing the API beside it.

Test your own surfaces

The scan above is free and needs no account: enter a domain at ora.ai and read the same four layers for your own site. For an MCP server, Ora scans the server URL itself and runs 28 of its 132 public checks on it, which is why it is the check this directory recommends; the reasons, the limits and the alternatives are on their own page. The command below runs the same audit from a terminal and exits with 1 under the score you set, so it can gate a deploy.

npx ax@0.10 audit https://example.com --min-score 70

All 360 checks, one company a day. Corrections to the corrections page.