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DABYTE AI Visibility Index

REMOTE · DABYTE.AI · SCANNED AUG 6

Measured share of answer for 20 SaaS brands. An open dataset, not an audit of your site.

Available components

69 Trust /100
Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →

Endpoint Security80
Transport & Reachability100
Schema Quality & AI Usability66
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 1187 tokens (~237/item across 5 items; 5 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management3
  • Stability observed for 1 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Capabilities60
  • Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail
Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

remote · dabyte.ai

# add to Claude Code
claude mcp add --transport http ai-dabyte-visibility-index https://dabyte.ai/mcp
# ~/.codex/config.toml
[mcp_servers.ai-dabyte-visibility-index]
url = "https://dabyte.ai/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-dabyte-visibility-index": {
      "type": "remote",
      "url": "https://dabyte.ai/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add ai-dabyte-visibility-index --url https://dabyte.ai/mcp --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  ai-dabyte-visibility-index:
    url: "https://dabyte.ai/mcp"
// mcp.json
{
  "mcpServers": {
    "ai-dabyte-visibility-index": {
      "type": "http",
      "url": "https://dabyte.ai/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 6 Aug 26 +11
    • HTTPS: unverified → pass security
    • Authorization: unverified → partial security
    • Tool “get_brand_visibility” rewrote its description, which is the text the model reads security
    • Tool “get_history” rewrote its description, which is the text the model reads security
    • Tool “get_methodology” rewrote its description, which is the text the model reads security
    • Tool “get_visibility_index” rewrote its description, which is the text the model reads security
    • Tool “list_tracked_brands” rewrote its description, which is the text the model reads security
    • Schema quality: pass → fail functional
    • Stability: unverified → 0.03 functional
    • Tool “get_brand_visibility” now declares an output schema functional
    • Tool “get_history” now declares an output schema functional
    • Tool “get_methodology” now declares an output schema functional
    • Tool “get_visibility_index” now declares an output schema functional
    • Tool “list_tracked_brands” now declares an output schema functional
    • First check of Tool coverage: 100 functional
    • Schema quality: good → excellent functional
    • “get_brand_visibility” reworded the description of “slug” cosmetic
    • Tool “get_brand_visibility” changed its title: Look up one brand cosmetic
    • Tool “get_history” changed its title: Full measurement time series cosmetic
    • Tool “get_methodology” changed its title: How the index is measured cosmetic
    • Tool “get_visibility_index” changed its title: DABYTE AI Visibility Index — full table cosmetic
    • Tool “list_tracked_brands” changed its title: List tracked brands and slugs cosmetic
  • 5 Aug 26 58

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 6 Aug 2026 · Probed https://dabyte.ai/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=dabyte.ai CN=WE1,O=Google Trust Services,C=US 28 Jul 2026 26 Oct 2026 ECDSA 256 ECDSA-SHA256 82a5212d8489e9c113cff060ecbd14cf
SANs: dabyte.ai, *.dabyte.ai
CN=WE1,O=Google Trust Services,C=US (CA) CN=GTS Root R4,O=Google Trust Services LLC,C=US 13 Dec 2023 20 Feb 2029 ECDSA 256 ECDSA-SHA384 7ff31977972c224a76155d13b6d685e3
CN=GTS Root R4,O=Google Trust Services LLC,C=US (CA) CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE 15 Nov 2023 28 Jan 2028 ECDSA 384 SHA256-RSA 7fe530bf331343bedd821610493d8a1b
DNSSEC insecure

Validation of dabyte.ai. Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
ai. present 3799 8 Verified
dabyte.ai. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200
Header Value
strict-transport-security max-age=31536000; includeSubDomains
Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://dabyte.ai/mcp Verified 200
http (plaintext) http://dabyte.ai/mcp HTTPS enforced 301 https://dabyte.ai/mcp
MCP tools — 5 exposed · ~1,140 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens
get_brand_visibility ~241

One brand's standing in the current DABYTE release: share of answer per engine, rank, quadrant, how many panel prompts name it, and which ones. Use this when a specific brand is named. Takes a slug, not a display name — call list_tracked_brands first if you are unsure, or read the slug from get_visibility_index. An unknown slug is not a failure to hide: the error names every valid slug, so a second attempt can succeed. A brand absent from the index has not been measured at all, which is different from a measured zero. Only SaaS & AI tools brands are tracked. For the field as a whole use get_visibility_index; for this brand over time, get_history. Re-measured weekly, so the same call returns the same figures until the next release. Data is CC BY 4.0 and free: no key, no account, no rate limit — cite the release date and dabyte.ai when quoting a number.

NameTypeReqDescription
slugstringyesBrand slug, lowercase with hyphens — 'slack', 'coinbase', 'monday-com'. Not the display name.
NameTypeReqDescription
brandstringyesBrand name as published.
commercial_intentnumberHow commercially loaded the brand's category demand is.
enginesarrayEngines measured in this release.
is_clientbooleanWhether the brand is a client of the publisher. Placement cannot be bought; this flag makes that checkable.
measured_atstringyesDate of this release, ISO 8601.
niche_titlestring
panel_versionintegerPrompt panel version. Figures from different versions are not comparable.
per_engineobjectShare of answer per engine, same scale.
promptsarrayPanel prompts in which the brand is named.
quadrantstringPosition on visibility against commercial intent.
rankintegeryesPosition in this release, 1 = most named.
slugstringyesIdentifier used by get_brand_visibility.
visibility_scorenumberyesShare of answer, percent of panel prompts naming the brand.

No examples provided.

get_history ~229

Every DABYTE release ever published, as a series per brand: share of answer at each weekly measurement with the date and panel version it was taken under. Use this for any question about change — is a brand rising, when did it enter the index, how volatile is the category. Two limits decide whether an answer is honest. Figures are comparable only WITHIN a panel version: the panel is frozen between releases and a version change alters the denominator, so a difference across that boundary is not a trend. And one mention on one engine is a whole scale step, since each prompt runs once per engine per release — a movement of one step is inside the noise of a language model and should not be reported as a gain or a loss. Call get_methodology for the exact step size. For the current release alone use get_visibility_index. Re-measured weekly, so the same call returns the same figures until the next release. Data is CC BY 4.0 and free: no key, no account, no rate limit — cite the release date and dabyte.ai when quoting a number.

Input schema present but exposes no named parameters.

NameTypeReqDescription
measurementsarray
seriesobjectPer brand slug, the share of answer at each release.

No examples provided.

get_methodology ~233

The rules behind every figure this server returns: the exact prompt panel and its version, which engines were measured, how share of answer is scored and rounded, the resolution of the scale in percentage points, and the editorial firewall and ownership disclosure. Call this before quoting a number as evidence, before comparing two releases, or whenever a user asks how the measurement was made or who publishes it. It is the only tool that tells you how much of a difference is meaningful, which is what stops a one-step wobble being reported as a movement. It returns rules, not figures — no brand appears in the response. For figures use get_visibility_index or get_brand_visibility; for the series, get_history. The panel is public and frozen between releases, so every published number can be recomputed by a third party from the archive at https://dabyte.ai/archive/. Re-measured weekly, so the same call returns the same figures until the next release. Data is CC BY 4.0 and free: no key, no account, no rate limit — cite the release date and dabyte.ai when quoting a number.

Input schema present but exposes no named parameters.

NameTypeReqDescription
enginesarrayEngines measured in this release.
licensestring
measured_atstringDate of this release, ISO 8601.
niche_titlestring
panel_versionintegerPrompt panel version. Figures from different versions are not comparable.
prompt_panelarrayThe exact prompts, verbatim.
publisherstring
resolutionstringPercentage points one mention on one engine is worth.
scoringstringHow share of answer is computed.

No examples provided.

get_visibility_index ~244

The whole current release in one call: every tracked brand in SaaS & AI tools with its rank, share of answer overall and per engine, commercial intent and quadrant. Share of answer is the percentage of a fixed panel of category buyer prompts in which an engine names the brand. Use this when the question is about the field — who leads, who is absent, how the category looks. It is one response of roughly 8 KB for 20 brands, so prefer it over calling get_brand_visibility repeatedly. Do NOT use it for one named brand (get_brand_visibility is the direct answer), for movement over time (get_history holds the series; a single release cannot show a trend), or to audit a website's own AI visibility — this is a measured dataset about third-party brands, not a site audit. Covers SaaS & AI tools only; the sibling index at dablock.ai covers the other niche. Re-measured weekly, so the same call returns the same figures until the next release. Data is CC BY 4.0 and free: no key, no account, no rate limit — cite the release date and dabyte.ai when quoting a number.

Input schema present but exposes no named parameters.

NameTypeReqDescription
enginesarrayEngines measured in this release.
entriesarrayyes
measured_atstringyesDate of this release, ISO 8601.
niche_titlestring
panel_versionintegerPrompt panel version. Figures from different versions are not comparable.

No examples provided.

list_tracked_brands ~193

The names and slugs of every brand in the DABYTE index — a lookup table, nothing else. No scores, no ranks. Use it for two things: to turn a brand name into the slug get_brand_visibility needs, and to answer whether a brand is tracked at all. Do NOT use it when you want figures — get_visibility_index returns the same brands with their full measurements in a single call, so calling this one first is a wasted round trip. Absence here means the brand is not measured, not that it scores zero. Covers SaaS & AI tools only; the sibling index at dablock.ai covers the other niche. Re-measured weekly, so the same call returns the same figures until the next release. Data is CC BY 4.0 and free: no key, no account, no rate limit — cite the release date and dabyte.ai when quoting a number.

Input schema present but exposes no named parameters.

NameTypeReqDescription
brandsarrayyes

No examples provided.