此 MCP 可以做什么
Provides an open dataset measuring AI answer visibility for 20 SaaS brands.
功能
工具
5
工具
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.
只读
幂等
输入模式
{'type': 'object', 'required': ['slug'], 'properties': {'slug': {'type': 'string', 'pattern': '^[a-z0-9-]{1,80}$', 'description': "Brand slug, lowercase with hyphens — 'slack', 'coinbase', 'monday-com'. Not the display name."}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'required': ['brand', 'slug', 'rank', 'visibility_score', 'measured_at'], 'properties': {'rank': {'type': 'integer', 'description': 'Position in this release, 1 = most named.'}, 'slug': {'type': 'string', 'description': 'Identifier used by get_brand_visibility.'}, 'brand': {'type': 'string', 'description': 'Brand name as published.'}, 'engines': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Engines measured in this release.'}, 'prompts': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Panel prompts in which the brand is named.'}, '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.'}, 'per_engine': {'type': 'object', 'description': 'Share of answer per engine, same scale.', 'additionalProperties': {'type': 'number'}}, 'measured_at': {'type': 'string', 'description': 'Date of this release, ISO 8601.'}, 'niche_title': {'type': 'string'}, 'panel_version': {'type': 'integer', 'description': 'Prompt panel version. Figures from different versions are not comparable.'}, 'visibility_score': {'type': 'number', 'description': 'Share of answer, percent of panel prompts naming the brand.'}, 'commercial_intent': {'type': 'number', 'description': "How commercially loaded the brand's category demand is."}}}
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {}, 'additionalProperties': False}
输出模式
{'type': 'object', 'properties': {'series': {'type': 'object', 'description': 'Per brand slug, the share of answer at each release.', 'additionalProperties': {'type': 'array'}}, 'measurements': {'type': 'array', 'items': {'type': 'object', 'properties': {'measured_at': {'type': 'string'}, 'panel_version': {'type': 'integer'}}}}}}
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {}, 'additionalProperties': False}
输出模式
{'type': 'object', 'properties': {'engines': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Engines measured in this release.'}, 'license': {'type': 'string'}, 'scoring': {'type': 'string', 'description': 'How share of answer is computed.'}, 'publisher': {'type': 'string'}, 'resolution': {'type': 'string', 'description': 'Percentage points one mention on one engine is worth.'}, 'measured_at': {'type': 'string', 'description': 'Date of this release, ISO 8601.'}, 'niche_title': {'type': 'string'}, 'prompt_panel': {'type': 'array', 'items': {'type': 'string'}, 'description': 'The exact prompts, verbatim.'}, 'panel_version': {'type': 'integer', 'description': 'Prompt panel version. Figures from different versions are not comparable.'}}}
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {}, 'additionalProperties': False}
输出模式
{'type': 'object', 'required': ['measured_at', 'entries'], 'properties': {'engines': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Engines measured in this release.'}, 'entries': {'type': 'array', 'items': {'type': 'object', 'required': ['brand', 'slug', 'rank', 'visibility_score'], 'properties': {'rank': {'type': 'integer', 'description': 'Position in this release, 1 = most named.'}, 'slug': {'type': 'string', 'description': 'Identifier used by get_brand_visibility.'}, 'brand': {'type': 'string', 'description': 'Brand name as published.'}, '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.'}, 'per_engine': {'type': 'object', 'description': 'Share of answer per engine, same scale.', 'additionalProperties': {'type': 'number'}}, 'visibility_score': {'type': 'number', 'description': 'Share of answer, percent of panel prompts naming the brand.'}, 'commercial_intent': {'type': 'number', 'description': "How commercially loaded the brand's category demand is."}}}}, 'measured_at': {'type': 'string', 'description': 'Date of this release, ISO 8601.'}, 'niche_title': {'type': 'string'}, 'panel_version': {'type': 'integer', 'description': 'Prompt panel version. Figures from different versions are not comparable.'}}}
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {}, 'additionalProperties': False}
输出模式
{'type': 'object', 'required': ['brands'], 'properties': {'brands': {'type': 'array', 'items': {'type': 'object', 'required': ['brand', 'slug'], 'properties': {'slug': {'type': 'string'}, 'brand': {'type': 'string'}}}}}}
历史
近期工具变更
已添加
get_methodology
2026年9月17日 07:56
已添加
get_history
2026年9月17日 07:56
已添加
list_tracked_brands
2026年9月17日 07:56
已添加
get_brand_visibility
2026年9月17日 07:56
已添加
get_visibility_index
2026年9月17日 07:56
发现
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