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DABYTE AI Visibility Index MCP server

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by dabyte.ai·ai.dabyte/visibility-index·v1.0.1
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Measured share of answer for 20 SaaS brands. An open dataset, not an audit of your site.

A89/100grade A
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DABYTE AI Visibility Index tools (5)

write = sends, deletes, buys or posts
  • get_brand_visibilityFree

    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.

  • get_historyFree

    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.

  • get_methodologyFree

    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.

  • get_visibility_indexFree

    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.

  • list_tracked_brandsFree

    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.

Public scan report

scanner v0.1.9 · 2026-09-24 · same rubric, same numbers if you re-run it

no findings
  • –Code scanremote-only server, no package to scann/a
  • Live reliabilityremote reachable in 540ms20/20
  • Tool poisoning5 tool descriptions checked15/15
  • Auth qualityopen endpoint, read-only tools10/15
  • Maintenancelast push 16 days ago15/15
  • Maintainer identitynamespace and repository owner differ; GitHub account older than a year; website matches verified namespace7/10
Overall 89/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How DABYTE AI Visibility Index compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
89/100
higher than 80% of 48,255 servers
Tools
5
the typical server has 7
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
Uptime
100%
of our recent checks; the typical remote server answers 100%
Response time
245 ms
faster than 56% of 30,031 servers

What its tools let an agent do: 5 read

Install DABYTE AI Visibility Index in Claude Code, Cursor or VS Code

claude mcp add --transport http visibility-index https://dabyte.ai/mcp
Add to Cursor

What the publisher says

From the DABYTE AI Visibility Index repository's README, as published. We do not edit it. Read it on GitHub

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:

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:

deltas are never computed across panel versions (methodology).

  • The panel is frozen between releases and any change bumps a panel version;

(dabyte archive, dablock archive), so any published delta can be recomputed by a third party.

  • Every past measurement is archived verbatim at a permanent URL

the index; every machine record carries an is_client flag so the claim is verifiable rather than rhetorical.

  • Placement cannot be bought. No brand can pay to enter, move inside, or leave

movements within one step are never reported as changes.

  • Measurement resolution is disclosed (one mention on one engine = one scale step);

Files

data/
  dabyte/    aiv.json · aiv.csv · history.json · rankings.json
  dablock/   aiv.json · aiv.csv · history.json · rankings.json
scripts/
  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 tools
https://dablock.ai/mcp    Crypto & Web3

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

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/.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

DABYTE AI Visibility Index: common questions

Is DABYTE AI Visibility Index MCP server safe?
Yes, by our scan: it is graded A (89/100). Read the DABYTE AI Visibility Index safety report
How do I install DABYTE AI Visibility Index?
It runs remotely at dabyte.ai. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
Does DABYTE AI Visibility Index need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is DABYTE AI Visibility Index maintained?
The last commit was 57 days ago (2026-09-08). The latest release is v1.0.1.
Is DABYTE AI Visibility Index up?
100% of our last 28 checks got an answer. We check remote servers about four times a day.
How does DABYTE AI Visibility Index compare with other MCP servers?
safety score 89/100 (higher than 80% of 48,255 servers); tools 5 (the typical server has 7); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.