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ENTIA Entity Verification

Name: ENTIA Entity Verification
Author: ENTIA-IA

Official

by ENTIA-IA

Overview Schema Source Related Servers Discussions Admin

Python

Remote

ENTIA MCP Server

面向 AI 代理的结构化商业智能。

ENTIA 提供覆盖 10 个国家的已验证实体数据——可通过模型上下文协议 (MCP) 或 REST API 访问。

指标	值
已验证实体	11,330,392
国家	10
BORME 商业登记行为	40.3M
医疗保健专业人士	570K+
MCP 工具	12
REST 端点	4

快速开始（< 2 分钟）

选项 1：远程 MCP 服务器（推荐）

无需安装。直接连接您的 MCP 客户端：

Claude Desktop — 添加到 claude_desktop_config.json：

{
  "mcpServers": {
    "entia": {
      "command": "npx",
      "args": ["mcp-remote", "https://mcp.entia.systems/mcp"]
    }
  }
}

Cursor IDE — 添加到 .cursor/mcp.json：

{
  "mcpServers": {
    "entia": {
      "command": "npx",
      "args": ["mcp-remote", "https://mcp.entia.systems/mcp"]
    }
  }
}

然后尝试：

Look up Telefonica in Spain

选项 2：REST API

# Search entities
curl "https://entia.systems/v1/search?q=telefonica&country=ES&limit=5" \
  -H "X-ENTIA-Key: YOUR_API_KEY"

# Full entity profile (BORME + GLEIF + VIES + Wikidata)
curl "https://entia.systems/v1/profile/Telefonica?country=ES"

# EU VAT verification
curl "https://entia.systems/v1/verify/vat/ESA28015865"

# Platform stats
curl "https://entia.systems/v1/stats"

选项 3：Python 客户端（本仓库中）

Python 客户端位于本仓库的 entia_mcp/ 目录下（将部分工具封装为便捷方法）。通过托管端点（选项 1）始终可以使用完整的 12 个工具。计划发布 PyPI 包。

Related MCP server: Bizfile MCP

12 个 MCP 工具

工具	功能
`entity_lookup`	按名称、CIF/NIF、欧盟增值税号或 LEI 验证任何企业的身份。交叉核对 BORME、VIES、GLEIF。
`search_entities`	按名称、关键字、国家或行业搜索 10 个国家的已验证实体。
`verify_vat`	通过 VIES（27 个成员国）进行实时欧盟增值税验证。
`zone_profile`	按邮政编码划分的西班牙社会经济概况（INE/SEPE/AEAT）：收入、就业、商业密度。
`get_competitors`	同一行业和地区的真实竞争对手。
`get_showcase`	精选 IBEX35 + 欧盟展示实体。免费，不消耗配额。
`professional_lookup`	验证 24 个西班牙健康/法律/心理垂直领域的专业注册。需要 DPA（GDPR 第 28 条）。
`get_full_dossier`	聚合器：一次调用获取实体的 90+ 个字段（结合 4 个 ENTIA 来源）。
`get_platform_stats`	实时平台统计：实体、国家、来源。
`run_risk_audit`	对任何域进行 AI 就绪性 + 数字风险审计。
`get_entia_home`	实体的完整 Schema.org JSON-LD @graph（Entia Home）。
`get_entity_home_projection`	Entia Home 记录的可机读投影（v1）。

定价

免费层：每月 100 次请求。权威定价实时发布在 entia.systems/.well-known/ai-pricing.json。

层级	价格	请求数	超额费用
TRACE	免费	100/月	硬限制
SIGNAL	29 欧元/月	500/月	硬限制
BUILD	99 欧元/月	2,500/月	硬限制
INTEGRATE	399 欧元/月	10,000/月	0.15 欧元/次
OPERATE	1,499 欧元/月	100,000/月	0.10 欧元/次
SCALE	2,500+ 欧元/月	500,000/月	0.05 欧元/次（联系）
ENTERPRISE	自定义	无限制	—

获取您的 API 密钥：entia.systems/mcp-setup

数据来源

所有数据均来自官方公共登记处：

BORME -- 西班牙商业登记处（BOE）
VIES -- 欧盟增值税验证（欧盟委员会）
GLEIF -- 法人实体标识符（全球 LEI 基金会）
Wikidata -- 知识图谱（维基媒体基金会）
REPS -- 西班牙医疗保健专业人士登记处
INE -- 西班牙国家统计局
SEPE -- 西班牙就业服务局
AEAT -- 西班牙税务局
Companies House -- 英国公司注册处
Sirene/INSEE -- 法国公司注册处

链接

关于

由 PrecisionAI Marketing OU（欧盟爱沙尼亚）构建。

增值税号：EE102780516
DUNS 编号：565868914
e-Residency 认证
符合 eIDAS 标准

许可证

代码：MIT（请参阅 LICENSE）。此服务器是一个轻量级 MCP 包装器：它使用 JSON-RPC 通信并代理到 ENTIA API。保持包装器开放是刻意的——它允许任何客户端准确审计发送和返回的内容。

数据：专有 — MIT 不适用于数据。 通过此服务器访问的已验证实体语料库单独许可，访问受 API 密钥控制。数据的使用受数据许可框架、MCP 条款和服务条款的约束，并受特殊数据库权（指令 96/9/EC）的保护。克隆此存储库不授予对语料库的任何权利。

Available Tools

6 tools

borme_lookupAInspect

Spanish mercantile acts from BORME (40M+ acts, 2009-2026).

Use when: user asks "who founded X?", "when was X incorporated?", "directors of Santander", "corporate history of Inditex". Returns: Acts count, key officers, founding date, corporate events.

Examples: borme_lookup("Telefonica") → 17,320 acts borme_lookup("A28015865") → Telefonica by CIF borme_lookup("Santander") → 50,722 acts

Args: query: Company name or Spanish CIF (without ES prefix, e.g. A28015865)

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description reveals key behavioral details: it covers 40M+ acts from 2009-2026, returns act count, key officers, founding date, and events. It also specifies the query format (CIF without ES prefix). This is transparent, though it could mention rate limits or data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, well-structured with line breaks for examples, and uses front-loaded purpose. Every sentence adds value; no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists (context signals), the description adequately covers input format, output summary (acts count, officers, events), and scope. It is complete for this simple tool with one parameter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The sole parameter 'query' has no schema description (0% coverage), but the description compensates fully by explaining it can be a company name or Spanish CIF without the ES prefix, with an example. This adds critical meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool looks up Spanish mercantile acts from BORME, providing specific use cases like 'who founded X?' and examples. It effectively distinguishes itself from sibling tools (e.g., entity_lookup, verify_vat) by focusing on BORME records.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes explicit usage triggers (e.g., 'when user asks...') and example queries, which is clear guidance. However, it lacks explicit when-not-to-use or alternative tools, so it is not a perfect 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

entity_lookupAInspect

Verify the identity of any business across 34 countries.

Use when: user asks "is this company legit?", "check CIF B80988678", "verify Telefonica". Returns: Trust Score 0-100, BORME acts count, LEI, Wikidata QID, jurisdiction.

Example: entity_lookup("Telefonica")

Args: query: Company name (Telefonica), CIF (A28015865), EU VAT (ESA28015865), or LEI (20 chars)

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.3/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses return fields and accepted input formats, but does not mention safety, authentication needs, or error behavior. It adds some value beyond schema but lacks depth for a no-annotation scenario.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (6 lines) and well-structured: purpose, usage conditions, return fields, example, and parameter description. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single parameter and presence of an output schema, the description covers input/output adequately and provides usage context. However, it lacks details on error handling or not-found cases, leaving minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by detailing the 'query' parameter: it accepts company name, CIF, EU VAT, or LEI, with examples. This is essential for correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Verify' and resource 'business identity' across 34 countries. It distinguishes itself from siblings like borme_lookup (BORME acts) and verify_vat (VAT) by focusing on identity verification with multiple identifiers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit 'Use when' with concrete user queries ('is this company legit?', 'check CIF B80988678'), giving clear context. While it doesn't explicitly state when not to use, the examples and sibling names imply alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_competitorsAInspect

Find competitors in the same sector and city.

Use when: user asks "who are the competitors?", "other dental clinics in Madrid", "similar businesses in Barcelona". Returns: Verified competitors with name, phone, website, address.

Examples: get_competitors("dental", "Madrid") get_competitors("legal", "Barcelona", limit=5)

Args: sector: Sector slug (dental, legal, reformas, estetica, veterinarios, asesorias, talleres, inmobiliarias, restaurantes, psicologia, gimnasios...) city: City name (Madrid, Barcelona, Valencia, Sevilla, Zaragoza...) country: ISO country code. Default: ES limit: Max results 1-50. Default: 10

ParametersJSON Schema

Name	Required	Default
`sector`	Yes
`city`	Yes
`country`	No	ES
`limit`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It states it returns 'Verified competitors with name, phone, website, address,' implying a read-only operation. While it doesn't detail authorization or rate limits, the behavior is sufficiently disclosed for a simple search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, well-structured with sections for usage, returns, and examples. Every sentence is meaningful, and there is no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, the description provides complete context: purpose, usage triggers, return format, and parameter details. The presence of an output schema reduces the need to explain return values, though the description already covers them.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully compensates by listing each parameter with examples, valid values (e.g., sector slugs, city names), defaults, and ranges. This adds significant meaning beyond the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Find competitors in the same sector and city,' providing a specific verb, resource, and scope. It distinguishes itself from sibling tools like borme_lookup or verify_vat, which serve different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use the tool with user query examples ('who are the competitors?'), but does not mention when not to use it or contrast with siblings. However, the context is clear enough for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_entitiesAInspect

Browse the entity registry by name, sector, or city.

Use when: user asks "find me a dentist in Madrid", "list lawyers in Barcelona", "show me car repair shops in Valencia". Returns: Verified entities with name, phone, website, address, sector.

Example: search_entities(q="dental", city="Madrid", limit=5)

Args: q: Search query — company name or keyword (dental, abogado, taller...) country: ISO country code (ES, GB, FR, DE, ...). Default: ES sector: Sector slug (dental, legal, reformas, estetica, veterinarios, asesorias...) city: City name (Madrid, Barcelona, Valencia, Sevilla...) limit: Max results 1-50. Default: 10

ParametersJSON Schema

Name	Required	Default
`q`	Yes
`country`	No	ES
`sector`	No
`city`	No
`limit`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description reveals that the tool returns verified entities and lists the fields. It could further disclose any rate limits, authentication requirements, or pagination behavior, but the provided details are adequate for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections for when to use, returns, and parameters. It is informative but slightly lengthy; a more concise wording could improve readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no annotations, output schema exists), the description covers purpose, usage, parameters, and return fields comprehensively. It addresses all key aspects an agent needs to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% coverage, but the description compensates fully by explaining each parameter: q, country (with default ES), sector (with examples), city, and limit (with range). It adds value beyond the schema by providing context and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool browses the entity registry by name, sector, or city, and provides concrete examples like 'find me a dentist in Madrid'. It distinguishes itself from sibling tools (e.g., entity_lookup) by focusing on broad search rather than specific lookups.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly specifies when to use the tool with example user queries. However, it does not explicitly state when not to use it or contrast with sibling tools like entity_lookup, which would help an agent decide between them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

verify_vatAInspect

Verify an EU VAT number via VIES (live, 27 member states, sub-second).

Use when: user asks "is this VAT valid?", "verify ESA28015865", "is this EU company registered?". Returns: valid (bool), legal name, registered address, country.

Examples: verify_vat("ESA28015865") → Telefonica SA — valid verify_vat("FR12345678901") → French company VAT check

Args: vat_id: Full EU VAT with country prefix (ESA28015865, FR12345678901, DE123456789)

ParametersJSON Schema

Name	Required	Description	Default
`vat_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries burden. It describes real-time live check, speed (sub-second), and return fields (valid, legal name, address, country). Lacks details on rate limits or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with purpose, usage, returns, and args. Some redundancy (examples repeated), but overall efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With one parameter and an output schema (implied), description explains return values adequately. Could mention VIES availability, but sufficient for a simple verification tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter, vat_id, with description explaining required format (country prefix, examples). Schema coverage is 0%, so description fully compensates with format and examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool verifies EU VAT numbers via VIES, with specific verb and resource, and distinguishes from sibling tools like borme_lookup and entity_lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells when to use: when user asks about VAT validity, verification, or EU company registration. Provides examples but does not explicitly mention when not to use, though context implies it's VAT-specific.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

zone_profileAInspect

Spanish socioeconomic data by postal code (INE/SEPE/AEAT/MITMA/MITECO).

Use when: user asks "what's the income level in 28001?", "unemployment rate in this area", "demographics of 08001 Barcelona". Returns: Median income (AEAT), unemployment (SEPE), population (INE), property price €/m² (MITMA), broadband coverage (MITECO).

Examples: zone_profile("28001") → Madrid Salamanca: income €99K, FTTH 99% zone_profile("08001") → Barcelona Eixample zone_profile("41001") → Sevilla Centro

Args: postal_code: Spanish 5-digit postal code (28001, 08001, 41001...)

ParametersJSON Schema

Name	Required	Description	Default
`postal_code`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the data sources and types of data returned. While it doesn't explicitly mention read-only behavior, rate limits, or data freshness, it is sufficiently transparent for a straightforward data retrieval tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (purpose, use when, returns, examples, args). Every sentence adds value, and the key information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (1 parameter, no nested objects, straightforward output), the description covers all needed aspects: what it does, when to use, input format, and output contents. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% but the description compensates fully by describing the only parameter 'postal_code' with format ('Spanish 5-digit postal code') and examples ('28001, 08001, 41001...'). This adds essential context beyond the schema's title and type.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'Spanish socioeconomic data by postal code' and lists specific data sources (INE/SEPE/AEAT/MITMA/MITECO) and metrics (income, unemployment, etc.). It clearly distinguishes from sibling tools (e.g., entity_lookup, borme_lookup) which target different domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit 'Use when' guidance with examples of user queries, and includes example inputs and outputs. This clearly indicates when the tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

20 tool updatesMay 3, 2026
- Changedborme_lookup6 fields changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
  - removedInput schema / properties / limit
```
Removed value: -{
-  "default": 20,
-  "description": "Max mercantile acts to return (1-50)",
-  "maximum": 50,
-  "minimum": 1,
-  "type": "integer"
-}
```
  - removedInput schema / properties / query / description
```
Removed value: -"Spanish CIF (e.g. B80988678) or company name"
```
  - addedInput schema / properties / query / title
```
Added value: +"Query"
```
  - addedInput schema / title
```
Added value: +"borme_lookupArguments"
```
  - addedOutput schema / title
```
Added value: +"borme_lookupDictOutput"
```
- Removedborme_new_constitutions
- Removedborme_officer_changes
- Changedentity_lookup6 fields changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
  - removedInput schema / properties / country
```
Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "ISO country code (ES, GB, FR...). Auto-detected from VAT prefix if not provided"
-}
```
  - removedInput schema / properties / query / description
```
Removed value: -"CIF (e.g. B80988678), EU VAT (e.g. ESB80988678, FR12345678901), LEI (20 alphanumeric chars), or company name"
```
  - addedInput schema / properties / query / title
```
Added value: +"Query"
```
  - addedInput schema / title
```
Added value: +"entity_lookupArguments"
```
  - addedOutput schema / title
```
Added value: +"entity_lookupDictOutput"
```
- Changedget_competitors13 fields changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
  - removedInput schema / properties / city / description
```
Removed value: -"City name (e.g. Madrid, Barcelona)"
```
  - addedInput schema / properties / city / title
```
Added value: +"City"
```
  - removedInput schema / properties / country / description
```
Removed value: -"ISO country code"
```
  - addedInput schema / properties / country / title
```
Added value: +"Country"
```
  - removedInput schema / properties / limit / description
```
Removed value: -"Max results (1-30)"
```
  - removedInput schema / properties / limit / maximum
```
Removed value: -30
```
  - removedInput schema / properties / limit / minimum
```
Removed value: -1
```
  - addedInput schema / properties / limit / title
```
Added value: +"Limit"
```
  - removedInput schema / properties / sector / description
```
Removed value: -"Business sector: dental, legal, estetica, psicologia, talleres, veterinarios, reformas, inmobiliarias, asesorias, gimnasios..."
```
  - addedInput schema / properties / sector / title
```
Added value: +"Sector"
```
  - addedInput schema / title
```
Added value: +"get_competitorsArguments"
```
  - addedOutput schema / title
```
Added value: +"get_competitorsDictOutput"
```
- Removedget_entity_home
- Removedget_platform_stats
- Removedmunicipality_profile
- Removedprofessional_lookup
- Removedsearch_dental_clinics_cataluna
- Changedsearch_entities15 fields changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
  - removedInput schema / properties / city / description
```
Removed value: -"City name (e.g. Madrid, Barcelona, London)"
```
  - addedInput schema / properties / city / title
```
Added value: +"City"
```
  - removedInput schema / properties / country / description
```
Removed value: -"ISO country code"
```
  - addedInput schema / properties / country / title
```
Added value: +"Country"
```
  - removedInput schema / properties / limit / description
```
Removed value: -"Max results (1-50)"
```
  - removedInput schema / properties / limit / maximum
```
Removed value: -50
```
  - removedInput schema / properties / limit / minimum
```
Removed value: -1
```
  - addedInput schema / properties / limit / title
```
Added value: +"Limit"
```
  - removedInput schema / properties / q / description
```
Removed value: -"Company name or partial name to search"
```
  - addedInput schema / properties / q / title
```
Added value: +"Q"
```
  - removedInput schema / properties / sector / description
```
Removed value: -"Business sector filter: dental, legal, estetica, psicologia, talleres, veterinarios, reformas, inmobiliarias, asesorias, gimnasios..."
```
  - addedInput schema / properties / sector / title
```
Added value: +"Sector"
```
  - addedInput schema / title
```
Added value: +"search_entitiesArguments"
```
  - addedOutput schema / title
```
Added value: +"search_entitiesDictOutput"
```
- Removedsearch_healthcare_centers
- Removedsearch_pharmacies
- Removedsearch_regcess
- Removedsearch_reps_by_specialty
- Removedverify_dentist
- Removedverify_healthcare_professional
- Removedverify_psychologist
- Changedverify_vat5 fields changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
  - removedInput schema / properties / vat_id / description
```
Removed value: -"EU VAT number with country prefix (e.g. ESB80988678, FR12345678901, DE123456789)"
```
  - addedInput schema / properties / vat_id / title
```
Added value: +"Vat Id"
```
  - addedInput schema / title
```
Added value: +"verify_vatArguments"
```
  - addedOutput schema / title
```
Added value: +"verify_vatDictOutput"
```
- Changedzone_profile5 fields changed
  - removedInput schema / additionalProperties
```
Removed value: -false
```
  - removedInput schema / properties / postal_code / description
```
Removed value: -"Spanish postal code (5 digits, e.g. 28001, 08001, 41001)"
```
  - addedInput schema / properties / postal_code / title
```
Added value: +"Postal Code"
```
  - addedInput schema / title
```
Added value: +"zone_profileArguments"
```
  - addedOutput schema / title
```
Added value: +"zone_profileDictOutput"
```
20 tool updatesv0.1.0Apr 13, 2026
- First observedborme_lookup
- First observedborme_new_constitutions
- First observedborme_officer_changes
- First observedentity_lookup
- First observedget_competitors
- First observedget_entity_home
- First observedget_platform_stats
- First observedmunicipality_profile
- First observedprofessional_lookup
- First observedsearch_dental_clinics_cataluna
- First observedsearch_entities
- First observedsearch_healthcare_centers
- First observedsearch_pharmacies
- First observedsearch_regcess
- First observedsearch_reps_by_specialty
- First observedverify_dentist
- First observedverify_healthcare_professional
- First observedverify_psychologist
- First observedverify_vat
- First observedzone_profile

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.4/5.0

Scored 2026-05-03 07:25 across 6 tools

Disambiguation4/5

Tools have mostly distinct purposes. `borme_lookup` focuses on Spanish mercantile acts, while `entity_lookup` provides broader verification across 34 countries. `get_competitors` and `search_entities` both search for businesses but with different focuses (competitors vs. general registry). `verify_vat` and `zone_profile` are clearly distinct.

Naming Consistency5/5

All tool names follow a consistent `verb_noun` pattern in snake_case (e.g., `borme_lookup`, `entity_lookup`, `get_competitors`). Verbs like lookup, get, search, verify are appropriate and descriptive of the action.

Tool Count5/5

With 6 tools, the server is well-scoped for entity verification. Each tool adds value without redundancy. The count is within the ideal range (3-15) and matches the domain's complexity.

Completeness4/5

Covers core verification workflows: entity lookup, VAT verification, competitor discovery, and registry search. Minor gaps include no direct tool for detailed corporate history or financial data, but these are reasonable omissions for the stated purpose.

Maintenance

ActivityMaintained

ResponsivenessUnresponsive

Resources

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EU-Verify Identity or Document Verification Service