Agent MCP Directory

monday.com: the 360 agent-readiness check

monday.com scores 88 of 100 on Ora's agent-readiness scan, an A, read 9 November 2026. Of the five surfaces an agent acts on, Ora found 4: an OpenAPI specification, a public API, OAuth, a command line. An A2A card, a WebMCP tool and an A, with the door unverified.

On 9 November 2026 the public site at monday.com scored 88 of 100 on Ora's agent-readiness scan, an A, in Ora's Productivity 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: The site offers strong agent-facing authentication and API access, and a GraphQL typed error model with rate-limit header documentation would round out agent support.

The score

monday.com on Ora, read 2026-11-09: points per layer, with the share of each layer's maximum. 59 checks pass, 13 are partial, 22 fail and 38 do not apply to this site.
LayerAsksPointsShare
UsabilityCan agents use it87 of 10087%
AccessCan agents read it56 of 6093%
DiscoveryCan agents find and recommend it15 of 1883%
PaymentsCan agents pay0 of 0none apply
TotalGrade A88 of 10088%

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.

In the directory, monday.com sign-in required, tools not seen, not counted; the connector run of 4 November 2026 is on the entry page. Ora's MCP server check for the same domain reads partial; 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: 19 checks Ora ran on monday.com, read 2026-11-09. The last column is Ora's own observation where it published one.
CheckResultPointsWhat Ora saw
MCP server / manifest mcp-serverPartial5 of 6MCP server detected at https://mcp.monday.com/mcp; it requires authentication. Presence is verified (5/6), but Ora could not inspect its tools or verify access scopes without credentials.
MCP well-known discovery mcp-well-known-discoveryPass2 of 2MCP server discoverable via server-card.json at /.well-known/mcp/
Public API with reachable endpoints public-apiPass7 of 7REST API documentation found at https://api.monday.com/v2/get_schema?format=sdl. GraphQL endpoint at https://api.monday.com/graphql is reachable; introspection requires authentication (API key / OAuth),
Public API/docs linked from homepage public-api-docsPass3 of 3Documentation site found at https://developer.monday.com
Developer portal developer-portalPass6 of 6Developer portal found at https://developer.monday.com
OpenAPI spec published openapi-specPass7 of 7OpenAPI spec found at https://monday.com/openapi.json (version: 3.1.0)
API catalog (RFC 9727) api-catalog-rfc9727Partial1 of 2api-catalog linkset[0] has no 'item' entries
A2A / agent-card a2a-agent-cardPass2 of 2A2A Agent Card found: "monday.com MCP Server"
Agent discovery file agent-discovery-filePass2 of 2Agent Skills index (agentskills.io) found at /.well-known/agent-skills/index.json with 2 skill(s)
OAuth 2.0 support oauth-supportPass5 of 5OAuth authorization server metadata at https://auth.monday.com/mcp
OAuth Protected Resource metadata (RFC 9728) oauth-protected-resourcePass2 of 2no detail published
auth.md exists auth-md-existsFail0 of 2No /auth.md found at site root
WebMCP support webmcpPass5 of 5Imperative WebMCP API detected (navigator.modelContext.registerTool in inline script). Note: the entry point moved to document.modelContext - Chrome 150+ deprecates the navigator.modelContext alias.
NLWeb /ask endpoint nlweb-askPass1 of 1NLWeb /ask endpoint exists but requires authentication (HTTP 403, via POST)
CLI tool available cli-toolPass3 of 3CLI package found on npm: @mondaycom/apps-cli
Multi-language SDK packages rest-sdk-packagesPartial1 of 3SDK package found only in npm
Rate limit response headers rate-limit-headersFail0 of 2GraphQL introspection auth-gated and no header convention documented on GraphQL-tagged pages
Idempotency-Key support idempotency-key-supportPass3 of 3no detail published
JSON error responses json-error-responsesPass4 of 4no detail published

At the door

What the site answers when a request arrives with an agent's user agent, and what robots.txt says to agents. 2 checks in this group do not apply to this site and are left out.

At the door: 6 checks Ora ran on monday.com, read 2026-11-09. The last column is Ora's own observation where it published one.
CheckResultPointsWhat Ora saw
robots.txt AI crawler policy robots-ai-policy-qualityPass2 of 2AI search crawlers: allowed in 18 of 18 checks (3 crawlers on 6 pages). AI training crawlers: allowed in 12 of 12 checks (2 crawlers on 6 pages), not scored.
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://monday.com/. Declared policy only;
Content behind auth docs-auth-gatePass2 of 2All 5 sampled pages are publicly readable (4 with substantive content)
Homepage not hidden from search noindex-directivesPass1 of 1No noindex on the homepage: no robots, googlebot or bingbot meta tag and no X-Robots-Tag header hides it from search.
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 monday.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-jsPartial1 of 3Homepage: 13923 chars with H1, but 3.0% content ratio is below the 5% target. Sampled pages with almost no text without JavaScript (1 of 5): https://monday.com/academy (69 chars).
Page token budget page-token-budgetPass1 of 1All 6 measured pages fit an agent context budget (largest ~4K tokens)
Sitemap exists sitemapPass2 of 2Valid sitemap found at https://monday.com/sitemap_index.xml with multiple sitemaps entries
Sitemap freshness (lastmod) sitemap-lastmodFail0 of 1None of the 338 sampled sitemap entries carries a lastmod date. Add <lastmod> (W3C datetime) so agents can prioritize fresh content.
llms.txt exists llms-txt-existsPass1 of 1Found the llms.txt at https://monday.com/llms.txt.
llms.txt formatting llms-txt-formattingPass2 of 2The llms.txt is well-formatted: 67 lines with markdown links, 9,893 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://monday.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 (ChatGPT-User, Claude-User, Perplexity-User) receives markdown when requesting HTML. Optional: detect AI-bot UAs server-side and serve them a markdown representation directly.
Agent mode view agent-mode-viewPartial1 of 2Agent mode view found at ?mode=agent (3 signals: mcp, agent, integration)
JSON-LD structured data json-ldPass4 of 4Rich JSON-LD identity: Organization with name, description, url, and sameAs/logo/address (1 block(s))
Organization schema completeness org-schema-completenessPass2 of 2no detail published
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", og:image, og:type
Agent instruction / when-to-use agent-instructionPass3 of 3no detail published

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 monday.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-accuracyPartial1 of 3monday.com ranks #7 for "monday.com" (searched your brand name alone: no main product term from your homepage qualified)
Wikipedia / Wikidata entity presence wikipedia-presencePass4 of 4Wikipedia "Monday.com" and Wikidata Q65073369 both verified - domain confirmed on both sources
Developer resource discoverability agentic-search-specificPass3 of 3no detail published
Listed in MCP registries mcp-registry-listedPass1 of 1no detail published
NPM/PyPI SDK package npm-sdk-packagePass1 of 1no detail published
ChatGPT app listed chatgpt-app-listedPass2 of 2no detail published
Registry branding registry-brandingPass2 of 2no detail published
Listed on skills.sh skills-sh-listedPass1 of 1no detail published
ARD discovery ard-catalogFail0 of 1No /.well-known/ard.json, no same-site rel="ard" link, 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. None of the 6 payment checks applied to monday.com.

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 monday.com, 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.

  • Brand name discoverability: partial, 1 of 3, about 2.5 points to gain. Ora saw: monday.com ranks #7 for "monday.com" (searched your brand name alone: no main product term from your homepage qualified)
  • GraphQL typed error model: fail, 0 of 3, about 1.3 points to gain. Ora saw: GraphQL introspection auth-gated and no typed graphql error model documentation found on GraphQL-tagged pages
  • ARD discovery: fail, 0 of 1, about 1.2 points to gain. Ora saw: No /.well-known/ard.json, no same-site rel="ard" link, and no legacy /.well-known/ai-catalog.json
  • Content without JavaScript: partial, 1 of 3, about 1.1 points to gain. Ora saw: Homepage: 13923 chars with H1, but 3.0% content ratio is below the 5% target. Sampled pages with almost no text without JavaScript (1 of 5): https://monday.com/academy (69 chars).
  • Schema type breadth: fail, 0 of 2, about 1.1 points to gain. Ora saw: No extended schema types found - AI can only answer basic questions about this entity

Our read

monday.com passes checks that almost nothing else in this directory passes. Beside the MCP server at mcp.monday.com/mcp, the server card at /.well-known/mcp/, OAuth metadata at auth.monday.com/mcp and an OpenAPI 3.1.0 specification at monday.com/openapi.json, Ora found an A2A agent card named for the MCP server, an agent skills index with two skills, a WebMCP tool registered in an inline script and an llms.txt at the root. The points left are the newer and smaller ones: the GraphQL endpoint documents no typed error model, there is neither an ARD catalog nor an extended schema type beyond the Organization block, and the home page's 13,923 characters are 3 percent of the page. One row is unverified rather than failed: the bot detection probe was stopped by a shield, a rate limit or a timeout, so whether the four agent user agents get in is an open question on this read. An A at 88, with the door the one thing to confirm.

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.