DABLOCK AI Visibility Index

ai.dablock由 dablock.ai 發布官方發布者v1.0.1更新於 Oct 25, 2026

Measured share of answer for 24 crypto and Web3 brands. An open dataset, not an audit of your site.

已驗證Streamable HTTP可網頁執行金融資料與分析AI 與機器學習

概覽

AI 產生的概覽

一個遠端 MCP 伺服器,提供公開的每週指數,衡量 AI 助理在買家提問中提及 24 個加密與 Web3 品牌的頻率。

可以做什麼
讀取目前完整發布:所有追蹤品牌的排名、整體及各引擎的答案佔比、商業意圖與象限,以及提及各品牌的提示詞面板和數字背後的方法說明。依 slug 查詢單一品牌的表現,或列出所有追蹤品牌及其 slug。取得歷次發布的歷史資料,依品牌提供含日期與面板版本的時間序列。
適用情境
適合回答關於加密或 Web3 品牌在 AI 助理中被提及情況、某品牌可見度排名或隨時間變化、以及某品牌是否被追蹤的問題。它是唯讀的參考資料集,並非對某個網站的稽核。
執行需求
位於 dablock.ai 的遠端端點,使用 streamable HTTP;未宣告需要安裝、API 金鑰或註冊。README 提到可自行以 Docker 架設,透過 HTTPS 讀取已發布的 JSON。
安裝前請注意
資料來自每個細分領域 16 條買家提示詞的固定版本面板,在 ChatGPT、Perplexity 和 Gemini 上量測;README 說明不跨面板版本計算差值,且一個刻度以內的變動不作為變化回報。README 稱排名位置不可購買,記錄帶有 is_client 標記,並聲明與同名公司無關聯。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 DABLOCK AI Visibility Index,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/ai.dablock%2Fvisibility-index/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "dablock-ai-visibility-index": {
      "type": "http",
      "url": "https://dablock.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.

來源:README.md,提交 2ab23a5

工具

5

get_visibility_index

DABLOCK AI Visibility Index — full table

The whole current release in one call: every tracked brand in crypto/Web3 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 24 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 crypto/Web3 only; the sibling index at dabyte.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 dablock.ai when quoting a number.

無需輸入參數。

get_brand_visibility

Look up one brand

One brand's standing in the current DABLOCK 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 crypto/Web3 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 dablock.ai when quoting a number.

輸入參數slug必填

list_tracked_brands

List tracked brands and slugs

The names and slugs of every brand in the DABLOCK 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 crypto/Web3 only; the sibling index at dabyte.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 dablock.ai when quoting a number.

無需輸入參數。

get_history

Full measurement time series

Every DABLOCK 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 dablock.ai when quoting a number.

無需輸入參數。

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://dablock.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 dablock.ai when quoting a number.

無需輸入參數。

版本歷史

1
  1. v1.0.1最新Sep 16, 2026

評分

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