DABYTE AI Visibility Index

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

我该使用它吗

质量与安全性

B
描述质量
100%
模式完整度
44%
命名质量
100%
投毒风险
80%
权限匹配度
100%
协议合规性
100%

发现(2)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool description contains URL to non-standard domain在 get_methodology 中

基于对工具定义和协议合规性的自动分析。

上下文开销

~2,356token 数(工具定义)
~2.6 KB典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 1.84%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

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

远程端点

https://dabyte.ai/mcpstreamable-http

它能做什么

工具清单

工具(5)

🟢 只读🟡 写入🔴 删除⚪ 未知
🟢get_visibility_index

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.

输入模式

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

输出模式

{
  "type": "object",
  "properties": {
    "measured_at": {
      "type": "string",
      "description": "Date of this release, ISO 8601."
    },
    "panel_version": {
      "type": "integer",
      "description": "Prompt panel version. Figures from different versions are not comparable."
    },
    "engines": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Engines measured in this release."
    },
    "niche_title": {
      "type": "string"
    },
    "entries": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "brand": {
            "type": "string",
            "description": "Brand name as published."
          },
          "slug": {
            "type": "string",
            "description": "Identifier used by get_brand_visibility."
          },
          "rank": {
            "type": "integer",
            "description": "Position in this release, 1 = most named."
          },
          "visibility_score": {
            "type": "number",
            "description": "Share of answer, percent of panel prompts naming the brand."
          },
          "per_engine": {
            "type": "object",
            "additionalProperties": {
              "type": "number"
            },
            "description": "Share of answer per engine, same scale."
          },
          "commercial_intent": {
            "type": "number",
            "description": "How commercially loaded the brand's category demand is."
          },
          "quadrant": {
            "type": "string",
            "description": "Position on visibility against commercial intent."
          },
          "is_client": {
            "type": "boolean",
            "description": "Whether the brand is a client of the publisher. Placement cannot be bought; this flag makes that checkable."
          }
        },
        "required": [
          "brand",
          "slug",
          "rank",
          "visibility_score"
        ]
      }
    }
  },
  "required": [
    "measured_at",
    "entries"
  ]
}
🟢get_brand_visibility(slug)

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.

输入模式

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "pattern": "^[a-z0-9-]{1,80}$",
      "description": "Brand slug, lowercase with hyphens — 'slack', 'coinbase', 'monday-com'. Not the display name."
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}

输出模式

{
  "type": "object",
  "properties": {
    "measured_at": {
      "type": "string",
      "description": "Date of this release, ISO 8601."
    },
    "panel_version": {
      "type": "integer",
      "description": "Prompt panel version. Figures from different versions are not comparable."
    },
    "engines": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Engines measured in this release."
    },
    "niche_title": {
      "type": "string"
    },
    "brand": {
      "type": "string",
      "description": "Brand name as published."
    },
    "slug": {
      "type": "string",
      "description": "Identifier used by get_brand_visibility."
    },
    "rank": {
      "type": "integer",
      "description": "Position in this release, 1 = most named."
    },
    "visibility_score": {
      "type": "number",
      "description": "Share of answer, percent of panel prompts naming the brand."
    },
    "per_engine": {
      "type": "object",
      "additionalProperties": {
        "type": "number"
      },
      "description": "Share of answer per engine, same scale."
    },
    "commercial_intent": {
      "type": "number",
      "description": "How commercially loaded the brand's category demand is."
    },
    "quadrant": {
      "type": "string",
      "description": "Position on visibility against commercial intent."
    },
    "is_client": {
      "type": "boolean",
      "description": "Whether the brand is a client of the publisher. Placement cannot be bought; this flag makes that checkable."
    },
    "prompts": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Panel prompts in which the brand is named."
    }
  },
  "required": [
    "brand",
    "slug",
    "rank",
    "visibility_score",
    "measured_at"
  ]
}
🟢list_tracked_brands

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.

输入模式

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

输出模式

{
  "type": "object",
  "properties": {
    "brands": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "brand": {
            "type": "string"
          },
          "slug": {
            "type": "string"
          }
        },
        "required": [
          "brand",
          "slug"
        ]
      }
    }
  },
  "required": [
    "brands"
  ]
}
🟢get_history

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.

输入模式

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

输出模式

{
  "type": "object",
  "properties": {
    "measurements": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "measured_at": {
            "type": "string"
          },
          "panel_version": {
            "type": "integer"
          }
        }
      }
    },
    "series": {
      "type": "object",
      "additionalProperties": {
        "type": "array"
      },
      "description": "Per brand slug, the share of answer at each release."
    }
  }
}
🟢get_methodology

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.

输入模式

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

输出模式

{
  "type": "object",
  "properties": {
    "measured_at": {
      "type": "string",
      "description": "Date of this release, ISO 8601."
    },
    "panel_version": {
      "type": "integer",
      "description": "Prompt panel version. Figures from different versions are not comparable."
    },
    "engines": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Engines measured in this release."
    },
    "niche_title": {
      "type": "string"
    },
    "prompt_panel": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "The exact prompts, verbatim."
    },
    "scoring": {
      "type": "string",
      "description": "How share of answer is computed."
    },
    "resolution": {
      "type": "string",
      "description": "Percentage points one mention on one engine is worth."
    },
    "license": {
      "type": "string"
    },
    "publisher": {
      "type": "string"
    }
  }
}

推荐提示词

retrieve_data
Get details about [item] from DABYTE AI Visibility Index
预期工具: get_visibility_index
fetch_info
Fetch [information type] using DABYTE AI Visibility Index
预期工具: get_visibility_index
list_items
List all [items] available in DABYTE AI Visibility Index
预期工具: list_tracked_brands
browse_collection
Show me the [collection] from DABYTE AI Visibility Index
预期工具: list_tracked_brands
explore_workflow
List available [items], then get details for each one using DABYTE AI Visibility Index
预期工具: list_tracked_brandsget_visibility_index

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证据

最近观测

已验证未记录版本5 个工具
已验证未记录版本5 个工具