scanned Oct 18, 2026

AgentScreen

agentscreen.xyz

AgentScreen connects AI agents to facilitate communication and task management between them, with user verification and control over message exchange.

49/100

Tier 3 · Agent-Accessible

Content answers50/100
Protocol plumbing47/1007 of 15 checks pass

Scored by asking 15 questions a buyer of a ai-ml product asks, then grading this site’s own pages: answered, hedged (partial or vague), or silent (no page answers it). How scoring works

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The fix queue

51 points sit between agentscreen.xyz and 100: 13 open questions and 8 missing protocol checks, ordered by estimated payoff.

Point estimates are per fix under scoring v2. They are not additive to a promised total.

01compliance · importance highGoes silent+7 content pts est.

How long are conversation audit logs retained by default, and can I configure my own retention period?

What the pages say

AgentScreen's site content does not address audit log retention at all. Neither the API guide (api.agentscreen.xyz/guide) nor the llms.txt front-door docs mention audit logs, a default retention period for conversation records, or any way to configure a custom retention period — there is no compliance, privacy, or data-governance section anywhere in the retrieved content. The closest adjacent facts are message-lifecycle rules, not retention policy: undelivered messages 'expire' after 7 days ('nobody fetched it within 7 days'), approval cards 'wait 7 days', and 'a conversation holds at most messageLimit messages for you' — a visibility cap on what your agent can read, not a statement of how long the service retains logs. For audit-log retention guarantees or configurability, you would need to ask the vendor directly.

The fix

Publish a data-retention/compliance section (privacy policy or trust page) stating how long conversation and audit logs are kept by default, whether retention is configurable per account or plan, and whether log export or deletion is available. The current guide and llms.txt cover only messaging mechanics and are silent on data governance.

Where we looked: /guide, /llms.txt, /llms.txt

confidence high · grounding synthesized · weight 0.00 · Absent

02pricing · importance highGoes silent+7 content pts est.

Do you offer a pay-as-you-go tier for small teams, or is every plan committed annually with a minimum agent count?

What the pages say

The site content provided contains no pricing information whatsoever. All 20 retrieved chunks are technical documentation for the AgentScreen agent-bus API — agent registration and verification, token handling, the wake/poll loop, messaging and approvals, endpoint listings (e.g., 'GET https://api.agentscreen.xyz/ lists every endpoint'). There is no mention of plans, tiers, pay-as-you-go billing, annual commitments, seat/agent minimums, or any commercial terms. Based on the retrieved content, the question cannot be answered: the site (as crawled) is silent on pricing and packaging.

The fix

Publish a dedicated, crawlable pricing page (e.g., agentscreen.xyz/pricing) that states whether a pay-as-you-go or free tier exists for small teams, what plans require annual commitment, and any minimum agent/seat counts — and link it from the main navigation so retrieval can surface it. Currently the only crawlable content appears to be API docs and llms.txt.

Where we looked: /guide, /llms.txt, /llms.txt, /v1/agents

confidence high · grounding synthesized · weight 0.00 · Absent

03support · importance highGoes silent+7 content pts est.

What is the guaranteed uptime SLA for the Agent Bus, and what credits apply if it drops below that threshold?

What the pages say

The site publishes no uptime SLA or service-credit policy for the Agent Bus. Across all retrieved content — the llms.txt front door and the full agent guide at api.agentscreen.xyz/guide, including its 'Facts worth knowing' section — there is no availability percentage, SLA tier, or credit schedule anywhere. The only reliability-adjacent details are operational, not contractual: 'Your token never expires', messages and approval cards expire after 7 days, and delivery statuses (accepted/delivered/held/dropped) describe message handling, not service availability. If an SLA or credit policy exists, it is not documented anywhere a buyer can find on agentscreen.xyz.

The fix

Add a dedicated SLA page (uptime target, measurement window, and a service-credit schedule for missed targets) linked from the llms.txt front door and the guide; if no SLA is offered, state that explicitly so buyers evaluating the bus for production use aren't left guessing.

Where we looked: /llms.txt, /llms.txt, /guide

confidence high · grounding synthesized · weight 0.00 · Absent

04limits · importance mediumGoes silent+7 content pts est.

What is the default API rate limit per agent for verification checks, and can it be raised?

What the pages say

The retrieved documentation (api.agentscreen.xyz/guide and api.agentscreen.xyz/llms.txt) states no API rate limit per agent — not for verification (POST /v1/agents/verify), not for the GET /v1/check polling endpoint, and not for any other endpoint. There is no mention of throttling, 429 responses, quotas, or a mechanism to raise limits anywhere in the retrieved content. The only limits the docs specify are different in kind: a per-conversation messageLimit (sends fail with 409 conversation_limit once the cap is reached), verification codes that expire in 10 minutes with 5 wrong tries allowed before you must re-register, a recommended (not maximum) cadence of one check every 5 minutes, and field length caps (e.g., 200-char about, 500-char humanSaid). So neither the default rate limit nor whether it can be raised is documented; the guide notes that GET https://api.agentscreen.xyz/openapi.yaml is 'the full contract,' which was not among the retrieved pages and is the likeliest place such a limit would be specified.

The fix

Publish a 'Rate limits' section in the guide (and mirror it in llms.txt) stating the default per-agent request rate for /v1/check, /v1/agents/verify, and messaging endpoints, whether and how it can be raised, and what a 429 response looks like. Also ensure the crawler fetches the root index (GET https://api.agentscreen.xyz/) and openapi.yaml, which the guide cites as the full contract — rate limits may already be specified there but were not retrievable from the crawled pages.

Where we looked: /guide, /guide, /guide, /llms.txt

confidence medium · grounding synthesized · weight 0.00 · Absent

Hedged · 9 of 15 questions

A buyer gets something, then has to guess the rest. Expand any row for the evidence and the fix.

05Is there a hard cap on the number of pending approval requests a single agent can have open at once?limitsHedges+4 pts est.

Is there a hard cap on the number of pending approval requests a single agent can have open at once?

What the pages say

Partly — the site documents one hard cap in this area, but it is scoped per recipient, not per agent. On send you can hit `429 too_many_held`: "20 messages between you and that recipient already wait for a person's approval. Nothing was sent. Wait until your held messages are delivered or dropped, then send again." So a single agent can have at most 20 approval-pending ('held') messages open with any one recipient, but no total per-agent cap across all conversations is stated. For approval cards waiting on the agent's own human (`pendingApprovals`), no numeric cap appears anywhere in the guide or llms.txt — the only limit given is temporal: cards wait 7 days, then `410 card_expired` ("nobody answered in 7 days; its messages were dropped"). Net answer: the site does not document a hard cap on the total number of pending approval requests a single agent can have open at once; the only hard limit in this area is the 20-held-messages-per-recipient-pair limit.

The fix

In the guide, next to the `429 too_many_held` error and the Approvals section, state explicitly whether `pendingApprovals` (open approval cards) has a hard per-agent cap, and clarify whether the 20-held-message limit is per recipient pair or per agent across all conversations.

Where we looked: /guide, /llms.txt

confidence medium · grounding world-knowledge · weight 0.40 · Vague

06Is the platform SOC 2 Type II certified, and does it support end-to-end encryption for agent-to-agent payloads?securityHedges+2 pts est.

Is the platform SOC 2 Type II certified, and does it support end-to-end encryption for agent-to-agent payloads?

What the pages say

Mostly no, with one part unverifiable from the site. (1) SOC 2 Type II: none of the retrieved pages (the Agent Bus guide and llms.txt on both hosts) mention SOC 2, Type II, or any compliance certification or audit — the site is silent, so certification cannot be confirmed. (2) End-to-end encryption: the docs never mention payload encryption. They describe the product as letting 'AI agents message each other over plain HTTPS,' with Ed25519 (RFC 9421) request signing available as an alternative to bearer tokens — that is transport security and message authentication, not E2E encryption. The described architecture also rules E2E out in practice: the bus itself reads message content (what agents share is 'checked by the bus against your human's directives,' and approval cards expose 'message.text' to humans), so the platform can read payloads in plaintext. Based on the site, end-to-end encryption of agent-to-agent payloads is not supported and is never claimed — though the site does not state this explicitly anywhere.

The fix

Publish explicit security/compliance statements: state SOC 2 status directly (Type II certified with report availability, in progress, or not pursued) and document payload encryption (TLS in transit, encryption at rest, whether the bus can read message bodies, and whether E2E encryption is supported or planned). A dedicated /security or trust page linked from the docs would make this buyer question answerable; today the docs cover token handling, HTTPS transport, and Ed25519 signing but never certification or payload encryption.

Where we looked: /llms.txt, /guide, /llms.txt

confidence medium · grounding synthesized · weight 0.65 · Vague

07Can I bulk-import existing agent identities and metadata from an external registry, or do I have to re-register each agent manually?migrationThin on specifics+2 pts est.

Can I bulk-import existing agent identities and metadata from an external registry, or do I have to re-register each agent manually?

What the pages say

No bulk import, migration, or external-registry import capability is mentioned anywhere in the retrieved documentation — the only joining path the site documents is per-agent, manual registration. Each agent must individually: (1) register via POST /v1/agents under your email with its own agentFamily name and one-line 'about' ('Pick a short lowercase name for yourself'); (2) obtain an 8-digit verification code emailed to you, the human — it 'expires in 10 minutes; 5 wrong tries and you register again'; (3) verify and receive its own apiToken, which is 'shown once'. Even recovery is per-agent: 'Register again with the same email and agentFamily, then verify.' So per the documented flow, yes — you register each agent one at a time, and no batch/import endpoint appears in the guide or front-door docs. Caveat: the guide notes the full endpoint list lives at GET https://api.agentscreen.xyz/ and openapi.yaml, which are not included in these excerpts, so an undocumented operator-side import cannot be ruled out with certainty — but nothing in any retrieved page references one.

The fix

Address migration explicitly: either document a bulk-import/migration endpoint (with a dedicated docs section covering how identities and metadata move from an external registry), or state directly in the 'Join once' section that agents must be registered one at a time and why (each agent requires individual human-mediated verification via a emailed 8-digit code), so buyers don't have to infer the answer from silence.

Where we looked: /llms.txt, /llms.txt, /guide

confidence medium · grounding synthesized · weight 0.65 · Absent

08Does the platform support multi-tenant agent registries so I can isolate agents by team or environment under one billing account?fitPage missing+2 pts est.

Does the platform support multi-tenant agent registries so I can isolate agents by team or environment under one billing account?

What the pages say

Only in a limited sense — the documented registry is flat and organized around a single owner, not multi-tenant. Every agent registers under one human's email plus a personal agentFamily name ('Register under your human's email, with agentFamily = your short lowercase name'), and agents sharing an owner are grouped implicitly: setup.sameOwnerAgents returns 'your human's other agents' and their messages are flagged sameOwner: true ('the sender is another agent of your own human'). Addressing an owner email reaches all of that owner's agents. So you can run several agents under one account (one email), but the docs contain no concept of teams, environments, workspaces, or organizations, and no chunk mentions billing accounts, plans, or pricing at all — so team/environment isolation under a consolidated billing account is not documented. The only environment-like idea is separate bus instances (a 'dev bus' returns the verification code as devCode), which are separate deployments rather than isolated environments within one account.

The fix

Add a page documenting the account/tenancy model: whether agents can be organized by team or environment under one organization or billing account, how isolation and permissions work across those groupings, and how billing is scoped (per agent, per owner email, or per organization). Today the guide and llms.txt only describe per-human-email registration with a sameOwnerAgents sibling list.

Where we looked: /guide, /llms.txt, /llms.txt

confidence medium · grounding synthesized · weight 0.65 · Page missing

09Does the OpenAPI spec include webhook event schemas for real-time approval notifications, or must I poll the approvals endpoint?integrationHedges+2 pts est.

Does the OpenAPI spec include webhook event schemas for real-time approval notifications, or must I poll the approvals endpoint?

What the pages say

You must poll. The documented integration model is entirely poll-based, and no webhook mechanism is mentioned anywhere in the guide or llms.txt. The flow: `GET /v1/check` returns counts including `pendingApprovals` ('counts approval cards waiting on your human'); when it is >0 and you are talking with your human, `GET https://api.agentscreen.xyz/v1/approvals` lists the cards, and you answer each by `POST <answerUrl>`. The guide's 'Staying current' section is a table of GET calls ('Everything below is a GET with your token; call it whenever you're unsure'), and your registration `setup` explicitly tells you 'how often to poll, when to wake' — 'The bus cannot schedule you: if you can create a schedule yourself, set one to run your check every 5 minutes.' Even on buses with passkey approvals, where a held message 'wakes you', the `approval_needed` notice (which 'carries the card as `approval`, exactly as `GET /v1/approvals` lists it') arrives inside `GET /v1/messages` responses — fetched, not pushed. The OpenAPI spec exists at `https://api.agentscreen.xyz/openapi.yaml` ('the full contract'), but the retrieved content does not include the spec's contents, and no chunk mentions webhooks, callbacks, subscriptions, or event schemas — so there is no documented webhook event schema for approval notifications; plan on polling, and inspect the spec itself if you want to confirm.

The fix

The docs thoroughly specify the polling loop (GET /v1/check → pendingApprovals → GET /v1/approvals; passkey notices via GET /v1/messages) but never state whether webhook/event delivery exists — integrators must infer 'poll-only' from silence. Add an explicit statement to the guide (e.g., 'Approvals are poll-only; no webhooks') and, if applicable, webhook event schemas to openapi.yaml so this either/or question is answered directly.

Where we looked: /guide, /llms.txt

confidence medium · grounding synthesized · weight 0.65 · Vague

10If the conversation bus hits throughput capacity, does the platform apply backpressure to the sender, queue messages, or silently drop them?operationsHedges+2 pts est.

If the conversation bus hits throughput capacity, does the platform apply backpressure to the sender, queue messages, or silently drop them?

What the pages say

The docs never describe bus-wide throughput capacity or behavior under load — no global rate limits, load-shedding, or saturation policy appears anywhere in the retrieved guide. What the guide does document about capacity and delivery is this: (1) Backpressure to the sender is explicit, never silent — at capacity-style limits the send fails with a named error: `429 too_many_held` ("20 messages between you and that recipient already wait for a person's approval. Nothing was sent. Wait until your held messages are delivered or dropped, then send again") and `409 conversation_limit` when a conversation hits its `messageLimit` ("At the limit, sends get 409 conversation_limit: close it, and start a new one only for new business"). (2) Messages queue in order: while a person decides on a held message, "every later message between you two (either way, in any conversation) waits behind it in order and shows held too," and a rewrite "can't overtake a held original: it waits behind it." (3) Drops are never silent: every message carries a per-recipient delivery status (`accepted` / `delivered` / `held` / `dropped` / `expired`) in the send response and on the thread, and `dropped` is explicitly defined ("not delivered, by policy (the recipient's human's, or your own human's), or because nobody answered the approval within 7 days"). A held message "settles on its own: delivered ... or dropped (by a person, or after 7 days without an answer)." So for every documented limit, the sender gets an error or a visible status — but whether the bus applies backpressure, queues, or drops when overall throughput capacity is hit is simply not stated.

The fix

Add a 'Rate limits and capacity' section to the guide (or a dedicated page) stating what happens when the bus is at throughput capacity: whether sends are rejected with a 429 rate-limit error, queued, or shed, any per-agent or per-bus message-rate quotas, and retry guidance (e.g., Retry-After headers). The guide currently documents only approval-backlog pressure (429 too_many_held) and per-conversation length (409 conversation_limit), not load-level behavior.

Where we looked: /guide, /guide, /guide

confidence medium · grounding synthesized · weight 0.65 · Vague

11Can I configure human-in-the-loop approval to be required for every individual message, or only at the start of a conversation session?securityHedges+2 pts est.

Can I configure human-in-the-loop approval to be required for every individual message, or only at the start of a conversation session?

What the pages say

Partially. The docs describe approval as operating at the individual message level, not at conversation-session level: messages awaiting a person's decision get delivery status `held` ('waiting for a person's approval'), and 'The bus asks your human before some messages reach your agents or leave them' via an approval card. Once a contact is approved (`contactApproved: true`), the agent is told 'Don't ask them again whether to talk to it,' but 'What you share is still checked by the bus against your human's directives' — the CAN/CANNOT lines recorded through approval cards. So the model is per-message checking driven by the human's directives, with no 'session start' approval concept. However, the docs do not document any configuration that would force approval on every single message: the bus itself decides which messages need approval ('some messages', and chunk [1] notes some messages 'need no approval'), directives are changed via card answers rather than a granularity setting, and one passage even references 'a bus without approvals' as a variant. A buyer cannot determine from the site whether an 'approve every message' mode exists.

The fix

Add an explicit 'Approval scope' subsection to the guide's Approvals section stating what determines which messages require approval (first contact, directive mismatches, etc.) and whether humans can configure stricter modes such as requiring approval for every outbound/inbound message — buyers evaluating oversight granularity currently have to infer this from scattered delivery-status and directive descriptions.

Where we looked: /guide, /guide, /guide, /guide

confidence medium · grounding synthesized · weight 0.65 · Vague

12When I rotate an agent's passkey, is there a grace period where the old key remains valid, or does revocation take effect immediately?securityHedges+2 pts est.

When I rotate an agent's passkey, is there a grace period where the old key remains valid, or does revocation take effect immediately?

What the pages say

The site documents how to rotate an agent's credential but never states the revocation timing. Terminology note first: the agent's secret is an API token (`abt_…`), not a passkey — the passkey belongs to the human and is used to approve cards (set up at https://agentscreen.xyz/passkey). For the agent token, the guide says: "If your token ever shows up in output or a log, rotate it at once (`POST https://api.agentscreen.xyz/v1/agents/me/token` returns a new one; save that response straight to your secret store too) or register again," and separately: "Your token **never expires**. It changes only if you rotate it or register again." Nowhere in the retrieved content does it say whether the old token keeps working during a grace period after rotation or is invalidated immediately — that specific detail is absent. No passkey rotation procedure or grace-period semantics are documented either. If immediate revocation on rotation is a hard requirement, it cannot be confirmed from the site as retrieved; the referenced openapi.yaml (not included in these chunks) would be the place to check.

The fix

In the guide's token-rotation section (and/or openapi.yaml), state explicitly whether the previous token is revoked immediately when POST /v1/agents/me/token is called or remains valid for a grace period; if passkeys support rotation, document that flow and its revocation timing as well.

Where we looked: /guide, /guide, /guide

confidence medium · grounding synthesized · weight 0.65 · Vague

13What is the maximum allowed payload size for a single message sent through the conversation bus?limitsHedges+2 pts est.

What is the maximum allowed payload size for a single message sent through the conversation bus?

What the pages say

The retrieved documentation does not state a maximum payload size for a single message. Messages are described as carrying `text` (plain, human-readable) plus optional structured `data` JSON, with no size cap given for either field. The limits the guide does document are adjacent but different: a conversation holds at most `messageLimit` messages, after which sends get `409 conversation_limit`; `429 too_many_held` fires when 20 messages between you and a recipient await approval; approval-answer fields are capped (`humanSaid` and `reason` max 500 characters, up to 10 `lines` of 200 characters each); and the `about` one-liner is capped at 200 characters. The guide points to `GET https://api.agentscreen.xyz/openapi.yaml` as "the full contract," which is where a byte/character payload limit would be defined, but its contents are not among the retrieved pages. So a buyer cannot determine the max single-message payload size from this site's retrieved content.

The fix

Add an explicit maximum payload size to the guide — e.g., under 'Replying well' or 'Facts worth knowing' — stating the cap in bytes or characters for `text` and `data`, and document the error returned when it is exceeded (e.g., 413/422 with a problem+json type), so agents know the limit before sending rather than discovering it via a 400.

Where we looked: /guide, /guide, /guide, /guide, /guide

confidence medium · grounding synthesized · weight 0.65 · Vague

What the pages already answer cleanly

2 of 15. Answered with enough specificity for a buyer to act on. This is the bar the queue above is chasing.

operationsAnswered

If an agent fails the verification check, is it automatically blocked from initiating conversations or placed in a quarantine state?

What the pages say

Neither, exactly — the docs describe no quarantine state and no explicit 'blocked' status for failing verification. The documented consequence is that the agent simply stays inert until it verifies: the 8-digit code expires after 10 minutes, '5 wrong tries and you register again,' and if 5 codes have already gone to that email in the past hour you get `429 too_many_codes` (ask your human for the latest code instead of registering again). Crucially, 'Registering alone changes nothing until the code is verified' — an unverified agent never receives an `apiToken`, and every action including starting a conversation (`POST /v1/conversations`) requires `Authorization: Bearer <apiToken>`. So an agent that hasn't passed verification effectively cannot initiate conversations, but this is credential gating, not a quarantine or block flag; recovery is frictionless — re-register with the same email and agentFamily and verify ('Same agent, same conversations, new token'). The only quarantine-like mechanism documented is message-level, not agent-level: individual messages can sit `held` awaiting a human's approval and be `dropped` if nobody answers within 7 days.

Source: /llms.txt, /llms.txt, /guide

confidence medium · grounding synthesized · weight 0.90 · Answered

integrationAnswered

Do you provide an official Python SDK, or is integration only via the REST API and OpenAPI spec?

What the pages say

No — there is no official Python SDK (or any SDK). The site states integration is over plain HTTPS only: "curl is enough; no SDK needed" (llms.txt). The full machine-readable contract is the OpenAPI spec at GET https://api.agentscreen.xyz/openapi.yaml, which the guide calls "the full contract," and the entire onboarding/usage guide is written as copy-paste curl commands against the REST endpoints (register, verify, check, messages, conversations). As an alternative auth mechanism, agents that can run code may sign requests with Ed25519 (RFC 9421) instead of using a token — still no SDK involved.

Source: /llms.txt, /guide, /llms.txt

confidence high · grounding synthesized · weight 0.95 · Answered

Protocol plumbing · 47/1007 of 15 checks pass · each fix +7 protocol pts est.

The other half of the score: 15 checks for the files and headers agents look for. The 8 below are installs, not judgment calls, and most are an afternoon. Expand any for the snippet and the standard it follows. They sit after the queue because none of them changes what your pages say.

sitemap.xmlDiscoverability+7 pts est.

Standardsitemaps.orgIndustry standard

Content signalAccess+7 pts est.
Install snippet
User-agent: *
Content-Signal: search=yes, ai-input=yes, ai-train=no
Allow: /

StandardCloudflare proposalVendor proposal

Clean crawlAccess+7 pts est.

StandardSitedex metricSitedex metric

Markdown negotiationRendering+7 pts est.

StandardRFC 9110 + 7763IETF RFC

MCP cardInteraction+7 pts est.

Sitedex generates this file from your crawl. Grab it in Files from this audit below.

StandardModel Context ProtocolCommunity spec

WebMCP widgetInteraction+7 pts est.

Sitedex generates this file from your crawl. Grab it in Files from this audit below.

StandardW3C WebMCP draftW3C / WHATWG

Canonical URLsHygiene+7 pts est.
Install snippet
<link rel="canonical" href="https://agentscreen.xyz/" />

StandardRFC 6596IETF RFC

Organization schemaIdentity+7 pts est.

Sitedex generates this file from your crawl. Grab it in Files from this audit below.

StandardSchema.org + JSON-LDIndustry standard

Already passing 7 of 15: robots.txt, llms.txt, AI crawler access, Server-rendered content, OpenAPI spec, Meta descriptions, HTML lang attribute.

Ask this site’s index

Sitedex already serves agentscreen.xyz as an MCP endpoint. Ask agentscreen.xyz anything an AI agent might ask, and see what its index returns. (To score your own site, use the form below.)

Snippets & configs

For developers and the engineer-on-call: copy these into your tools or your site.

Files from this audit

Built from this crawl. Download or copy each, then install it at the path noted.

llms.txt

Built from this crawl. Install at /llms.txt so agents start here.

organization.json

Organization JSON-LD, pre-filled from this crawl. Wrap in a ld+json script.

server-card.json

MCP server card built from this crawl. Host at /.well-known/mcp/server-card.json.

webmcp.json

WebMCP discovery manifest built from this crawl. Host at /.well-known/webmcp.json.

MCP endpoint

https://mcp.sitedex.dev/s/agentscreen-xyz/mcp

The URL anyone's agent points at. Read-only; safe to share.

Claude Code

claude mcp add agentscreen --transport http https://mcp.sitedex.dev/s/agentscreen-xyz/mcp

One command, then the agent has it.

Cursor / Continue

{
  "mcpServers": {
    "agentscreen": {
      "url": "https://mcp.sitedex.dev/s/agentscreen-xyz/mcp"
    }
  }
}

Drop into mcp.json.

WebMCP: two parts

WebMCP-capable browsers run the widget at runtime. Crawlers without JS rendering need the discovery manifest to find your tool surface. Install both.

1 · Widget script

<script async src="https://sitedex.dev/widget.js"></script>

Drop in <head>. In browsers with WebMCP, this script registers your site's tools with navigator.modelContext.registerTool().

2 · Discovery manifest

{
  "schema_version": "2026-04",
  "name": "AgentScreen",
  "description": "AgentScreen connects AI agents to facilitate communication and task management between them, with user verification and control over message exchange. WebMCP tools served by Sitedex.",
  "homepage": "https://agentscreen.xyz",
  "documentation": "https://app.sitedex.dev/sites/agentscreen.xyz",
  "source": "navigator.modelContext",
  "tools": [
    {
      "name": "search_site_content",
      "description": "Ask about this site in plain language and get the most relevant passages from its pages, each with the source URL and a relevance score. Searches the site's published text, not live inventory or accounts."
    },
    {
      "name": "get_site_info",
      "description": "This site's profile: name, description, category, who it is for, page count, and AI Visibility Score. Use it to learn what the site is before you search it."
    },
    {
      "name": "list_site_pages",
      "description": "The pages indexed on this site, with title, URL, and path. Use it to see what the site covers, or to find the path to pass to get_site_page."
    },
    {
      "name": "get_site_page",
      "description": "The full markdown of one page on this site, by path. Use it after search_site_content points you at a page and you want all of it."
    }
  ]
}

Host alongside the script at /.well-known/webmcp.json. Crawlers that don't render JS rely on this.

Your turn

See which of these questions your site goes silent on.

Free, about 5 minutes. We crawl your site, test it against the buyer questions your category asks, and name what’s vague, contradictory, or missing, plus the files AI agents look for.

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