DABYTE AI Visibility Index

ai.dabytePublished by dabyte.aiOfficial publisherv1.0.1Updated Nov 3, 2026

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

VerifiedStreamable HTTPWeb executableData & AnalyticsBusiness & Commerce

Overview

AI-generated overview

Read-only access to the DABYTE AI Visibility Index: weekly measured share of answer for 20 SaaS and AI-tool brands across ChatGPT, Perplexity and Gemini.

What you can do
  • Retrieve the full current release with ranks, share of answer overall and per engine, commercial intent and quadrant
  • Look up one brand's standing, including which panel prompts name it
  • List tracked brand names and slugs for lookup
  • Read the full weekly history series per brand, with dates and panel versions
  • Read the methodology: prompt panel, engines measured, scoring and rounding rules
When to use it
Useful when answering questions about how often AI assistants name a SaaS or AI-tool brand, comparing brands, or tracking visibility trends over time. Also handy for citing the measurement rules behind those figures.
Requirements
A remote MCP endpoint at dabyte.ai; no installation, API key or sign-up is needed. A self-hosted Docker option reads the published JSON over HTTPS.
Before you install
The data covers only 20 SaaS and AI-tool brands measured on a fixed 16-prompt panel, so it is an open dataset rather than an audit of a specific site. Deltas are not comparable across panel versions, and movements within one scale step are not reported as changes. The README notes a similarly named, unaffiliated company.

Installation

In SourceWeft

  1. Open DABYTE AI Visibility Index in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.dabyte%2Fvisibility-index/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "dabyte-ai-visibility-index": {
      "type": "http",
      "url": "https://dabyte.ai/mcp"
    }
  }
}

README

AI Visibility Index — open weekly data (dabyte.ai · dablock.ai)

Weekly measurements of which brands AI assistants actually name when a buyer asks a category question — published as open data by VECTORY on two data desks:

SiteNicheBrandsLive data
dabyte.aiSaaS & AI tools20aiv.json · history · CSV
dablock.aiCrypto & Web324aiv.json · history · CSV

This repository is a mirror for discovery and reproducibility. The canonical, always-current data lives on the domains above — no key, no sign-up, machine-first (JSON, CSV, markdown mirrors, llms.txt, MCP tools at /.well-known/mcp.json).

What is measured

Share of answer: the percentage of a fixed panel of category buyer prompts (16 per niche, frozen and versioned) in which an answer engine names the brand. Engines measured: ChatGPT (OpenAI), Perplexity, Google Gemini — each prompt run per engine, per release, weekly.

Example, measured 2026-08-04 (panel v2, first 3-engine release):

  • dabyte.ai — Slack 33.3% · Notion 29.2% · HubSpot 22.9%
  • dablock.ai — Coinbase 41.5% · Binance 26.9% · Kraken 25.0%

Rules that make the numbers citable:

  • The panel is frozen between releases and any change bumps a panel version; deltas are never computed across panel versions (methodology).
  • Every past measurement is archived verbatim at a permanent URL (dabyte archive, dablock archive), so any published delta can be recomputed by a third party.
  • Placement cannot be bought. No brand can pay to enter, move inside, or leave the index; every machine record carries an is_client flag so the claim is verifiable rather than rhetorical.
  • Measurement resolution is disclosed (one mention on one engine = one scale step); movements within one step are never reported as changes.

Files

data/  dabyte/    aiv.json · aiv.csv · history.json · rankings.json  dablock/   aiv.json · aiv.csv · history.json · rankings.jsonscripts/  fetch_latest.py   — refresh this mirror from the live endpoints

aiv.json — current measurement: per-brand share of answer overall and per engine, rank, commercial-intent score, quadrant, panel version. history.json — full per-brand time series across all published measurements. rankings.json — derived rankings (most visible, invisible-despite-demand, movers).

Citation

DABYTE AI Visibility Index — SaaS & AI Tools, 2026-08-04. dabyte.ai

DABLOCK AI Visibility Index — Crypto & Web3, 2026-08-04. dablock.ai

Two licences, because this repository holds two different things. The datasets under data/ are CC BY 4.0 (data/LICENSE) — free for any use, including commercial, with attribution. The code (scripts/, mcp-server/) is MIT (LICENSE).

MCP server

The index is also an MCP server, so an assistant can query it directly. Hosted endpoints need no installation:

https://dabyte.ai/mcp     SaaS & AI toolshttps://dablock.ai/mcp    Crypto & Web3

To run your own — no dataset required, it reads the published JSON over HTTPS:

bash
docker build -t aiv-mcp . && docker run -p 8090:8090 aiv-mcp

Tool reference and client setup: mcp-server/README.md.

Disambiguation

dabyte.ai is not affiliated with databyte.tech, DataByte, or any similarly named company. dablock.ai is not affiliated with dablock.com. Both are data desks published by VECTORY; the AI Visibility Index lives only at https://dabyte.ai/ and https://dablock.ai/.

Contributing data

Companies can contribute their own primary datasets (observed pricing, discount bands, usage telemetry, benchmark results) for free open publication with attribution — see dabyte.ai/contribute and dablock.ai/contribute. Contributing never affects a score in the index.

Source: README.md at commit 2ab23a5

Tools

5

get_visibility_index

DABYTE AI Visibility Index — full table

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.

Takes no parameters.

get_brand_visibility

Look up one brand

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.

Parametersslugrequired

list_tracked_brands

List tracked brands and slugs

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.

Takes no parameters.

get_history

Full measurement time series

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 small moves sit inside language-model noise: since panel v3 (2026-08-10) each prompt runs three times per engine per release and the figure is the share of runs; earlier releases ran each prompt once, so one mention on one engine was a whole scale step there. Either way a one-step movement 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.

Takes no parameters.

get_methodology

How the index is measured

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.

Takes no parameters.

Version history

1
  1. v1.0.1LatestSep 16, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts