WatchBase Data Feed API에 대한 액세스를 제공하여 시계 메타데이터를 쿼리할 수 있는 MCP(Model Context Protocol) 서버입니다.
WatchBase 데이터 피드 API는 브랜드, 제품군(컬렉션), 특정 시계 모델, 참조 번호, 기술 세부 정보, 이미지 등 포괄적인 시계 정보 데이터베이스에 대한 체계적인 액세스를 제공합니다. 개발자는 이를 통해 상세한 시계 데이터를 애플리케이션에 통합할 수 있습니다. 자세한 내용은 WatchBase API 문서 에서 확인할 수 있습니다.
Related MCP server: mcp-mediawiki-crunchtools
이 MCP 서버는 WatchBase API 엔드포인트에 해당하는 다음 도구를 제공합니다.
search : 브랜드 이름, 제품군 이름, 시계 이름, 참조 번호(전체 단어와 일치)로 데이터베이스를 검색합니다.
search_refnr : 참조 번호로 데이터베이스를 검색합니다(부분 일치 허용).
list_brands : 데이터베이스에 있는 모든 시계 브랜드 목록을 검색합니다.
list_families : 주어진 브랜드 ID에 대한 모든 제품군(컬렉션) 목록을 검색합니다.
list_watches : 특정 브랜드 ID 및 선택적으로 제품군 ID에 해당하는 시계 목록을 가져옵니다. 업데이트 날짜별로 필터링할 수 있습니다.
get_watch_details : WatchBase ID를 사용하여 특정 시계의 전체 세부 정보(모든 데이터 필드)를 검색합니다.
Node.js 및 npm: 종속성을 설치하고 서버를 실행하는 데 필요합니다.
WatchBase API 키: WatchBase의 API 키가 필요합니다. WatchBase API 페이지를 방문하여 액세스를 요청하고 키를 받으세요.
저장소를 복제합니다.
지엑스피1
종속성 설치:
npm install서버를 빌드하세요:
npm run build이 명령은 TypeScript 소스 코드를 JavaScript로 컴파일하고 출력을 build/ 디렉토리(특히 build/index.js )에 저장합니다.
서버를 사용하려면 WATCHBASE_API_KEY 환경 변수를 통해 WatchBase API 키를 제공해야 합니다. MCP 클라이언트(예: Cline/Roo Code 또는 Claude Desktop App)에서 이 서버를 실행하고 환경 변수를 전달하도록 구성해야 합니다.
구성 예:
다음은 일반적인 MCP 클라이언트의 예입니다. /path/to/your/watchbase-mcp/build/index.js 시스템에서 컴파일된 서버 파일의 실제 절대 경로로 바꾸고, YOUR_WATCHBASE_API_KEY 실제 WatchBase API 키로 바꾸세요.
MCP 서버용 VS Code 설정을 엽니다. macOS에서는 일반적으로 ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json 에 있습니다 . (참고: 정확한 경로는 운영 체제 및 VS Code 설치 유형에 따라 다를 수 있습니다. Roo Code의 경우 saoudrizwan.claude-dev rooveterinaryinc.roo-cline 으로 변경하세요.)
mcpServers 키 아래에 다음 구성 블록을 추가합니다.
"watchbase-mcp": {
"command": "node",
"args": ["/path/to/your/watchbase-mcp/build/index.js"], // <-- IMPORTANT: Replace with the ACTUAL absolute path to build/index.js
"env": {
"WATCHBASE_API_KEY": "YOUR_WATCHBASE_API_KEY" // <-- IMPORTANT: Replace with your WatchBase API Key
},
"disabled": false,
"autoApprove": [] // Or add specific tools you want to auto-approve
}Claude Desktop App 구성 파일을 엽니다. macOS에서는 일반적으로 ~/Library/Application Support/Claude/claude_desktop_config.json 에 있습니다 . (참고: 정확한 경로는 운영 체제에 따라 다를 수 있습니다.)
mcpServers 키 아래에 다음 구성 블록을 추가합니다.
"watchbase-mcp": {
"command": "node",
"args": ["/path/to/your/watchbase-mcp/build/index.js"], // <-- IMPORTANT: Replace with the ACTUAL absolute path to build/index.js
"env": {
"WATCHBASE_API_KEY": "YOUR_WATCHBASE_API_KEY" // <-- IMPORTANT: Replace with your WatchBase API Key
},
"disabled": false,
"autoApprove": [] // Or add specific tools you want to auto-approve
}구성이 완료되면 use_mcp_tool 명령/도구를 사용하여 AI 어시스턴트에서 서버 도구를 호출할 수 있습니다.
search 예시<use_mcp_tool>
<server_name>watchbase-mcp</server_name>
<tool_name>search</tool_name>
<arguments>
{
"q": "priors court"
}
</arguments>
</use_mcp_tool>search_refnr 번호 예시<use_mcp_tool>
<server_name>watchbase-mcp</server_name>
<tool_name>search_refnr</tool_name>
<arguments>
{
"q": "P2/"
}
</arguments>
</use_mcp_tool>list_brands 예시<use_mcp_tool>
<server_name>watchbase-mcp</server_name>
<tool_name>list_brands</tool_name>
<arguments>
{}
</arguments>
</use_mcp_tool>list_families 예제<use_mcp_tool>
<server_name>watchbase-mcp</server_name>
<tool_name>list_families</tool_name>
<arguments>
{
"brand_id": 37
}
</arguments>
</use_mcp_tool>list_watches 예제<use_mcp_tool>
<server_name>watchbase-mcp</server_name>
<tool_name>list_watches</tool_name>
<arguments>
{
"brand_id": 37,
"family_id": 279
}
</arguments>
</use_mcp_tool>get_watch_details 예제<use_mcp_tool>
<server_name>watchbase-mcp</server_name>
<tool_name>get_watch_details</tool_name>
<arguments>
{
"id": 17289
}
</arguments>
</use_mcp_tool>이 MCP 서버 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다. 자세한 내용은 라이선스 파일을 참조하세요.
API 사용과 관련하여 WatchBase 서비스 약관도 참조하세요.
Retrieve the full details for a particular watch by its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ID of the watch |
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 states the action ('Retrieve') but doesn't disclose behavioral traits like whether this is a read-only operation, error handling for invalid IDs, authentication needs, rate limits, or response format. This leaves significant gaps for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with zero waste, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'full details' include, error scenarios, or return values, which are crucial for a retrieval tool. With low contextual support from structured fields, the description should provide more completeness but fails to do so.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'id' parameter documented as 'ID of the watch'. The description adds no additional meaning beyond this, such as format examples or constraints, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieve') and resource ('full details for a particular watch'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_watches' or 'search', which might also retrieve watch information but with different scopes or filters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'list_watches' or 'search'. It mentions retrieving details by ID, but doesn't clarify if this is for single-item lookups or when other tools might be more appropriate, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve a list of all brands in the database.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a retrieval operation but doesn't mention important behavioral aspects like whether results are paginated, sorted, limited in count, or if authentication is required. For a list operation with zero annotation coverage, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states exactly what the tool does with no wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list retrieval tool with no annotations and no output schema, the description is insufficiently complete. It doesn't describe what format the list returns (e.g., array of brand objects with specific fields), whether there are limitations on the result set, or how the tool behaves in different scenarios. The simplicity of having zero parameters doesn't compensate for these gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100%, so there are no parameters to document. The description appropriately doesn't attempt to explain nonexistent parameters, earning a baseline score of 4 for this dimension.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve a list') and resource ('all brands in the database'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_families' or 'list_watches' that likely follow similar patterns for different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'search' or 'get_watch_details'. It doesn't mention whether this is for browsing all brands versus filtered searches, or what context would make this the appropriate choice among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve a list of all families for a given brand.
| Name | Required | Description | Default |
|---|---|---|---|
| brand_id | Yes | BrandID of the brand |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a retrieval operation but doesn't mention whether it's paginated, rate-limited, requires authentication, returns structured data, or has any side effects. For a list operation with zero annotation coverage, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple list operation and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what a 'family' represents in this domain, what format the returned list takes, or how this tool relates to sibling tools like 'list_watches'. The agent would need to guess about important contextual details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'brand_id' clearly documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline score when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieve') and resource ('list of all families for a given brand'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from its sibling 'list_brands' or 'list_watches', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_brands' or 'list_watches'. It mentions the required 'brand_id' parameter but doesn't explain the relationship between brands, families, and watches, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve a list of watches for a particular Brand and/or Family, optionally filtered by update date.
| Name | Required | Description | Default |
|---|---|---|---|
| brand_id | Yes | BrandID of the brand | |
| family_id | No | Optional: FamilyID of the family | |
| updated_since | No | Optional: Limit results to watches updated after this date (YYYY-MM-DD) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the retrieval action but doesn't mention pagination, rate limits, authentication needs, error conditions, or what happens when no matches are found. For a list operation with 3 parameters, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and includes all key filtering options. There's zero waste or redundancy, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list retrieval tool with 3 parameters and no annotations or output schema, the description is incomplete. It doesn't address behavioral aspects like pagination, sorting, response format, or error handling. While the purpose is clear, the lack of context about how the tool behaves in practice leaves significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds marginal value by clarifying that filtering is by 'Brand and/or Family' and 'optionally filtered by update date', but doesn't provide additional semantics beyond what the schema already specifies. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieve') and resource ('list of watches') with specific filtering criteria ('for a particular Brand and/or Family, optionally filtered by update date'). It distinguishes from siblings like 'get_watch_details' (single watch) and 'list_brands/families' (different resources), but doesn't explicitly contrast with 'search' or 'search_refnr' which might overlap in functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'search' or 'search_refnr'. It mentions optional filtering by update date, but doesn't clarify use cases, prerequisites, or exclusions. The agent must infer usage from the name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the database by brand name, family name, watch name and reference number (whole words).
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search keywords |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'whole words' matching, which is useful context beyond the schema. However, it doesn't describe other important behaviors like pagination, result format, error handling, or performance characteristics, leaving significant gaps 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that clearly states the purpose and key constraint ('whole words'). Every word earns its place with no redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 1 parameter (100% schema coverage) but no annotations and no output schema, the description provides adequate basic information about search fields and matching behavior. However, it lacks details about result structure, limitations, or error cases that would be helpful given the absence of structured output documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'q' parameter as 'Search keywords'. The description adds value by specifying what fields are searched (brand name, family name, watch name, reference number) and the 'whole words' matching behavior, but doesn't provide additional syntax or format details beyond what the schema implies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches a database using specific fields (brand name, family name, watch name, reference number) and specifies 'whole words' matching. It distinguishes from siblings like 'list_brands' or 'get_watch_details' by being a general search, though it doesn't explicitly differentiate from 'search_refnr' which appears to be a more specialized search tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching by specific fields with whole-word matching, but doesn't explicitly state when to use this tool versus alternatives like 'search_refnr' or 'list_watches'. It provides some context (searching by multiple fields) but lacks clear exclusions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the database by reference number (allows partial matches).
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search keywords (reference number) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the partial match capability. It doesn't disclose whether this is a read-only operation, what permissions are needed, how results are returned (format, pagination), or any rate limits. The description adds minimal behavioral context beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core function and includes the key behavioral detail (partial matches) without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with one parameter and no output schema, the description covers the basic purpose and partial match behavior adequately. However, with no annotations and no output schema, it lacks details on return format, error conditions, or operational constraints that would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, with the parameter 'q' documented as 'Search keywords (reference number)'. The description adds that it allows partial matches, which provides useful context beyond the schema, but doesn't elaborate on syntax or format requirements. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search') and resource ('database by reference number'), with the specific capability of partial matches. It distinguishes from the generic 'search' sibling by specifying reference number searches, though it doesn't explicitly contrast with other siblings like list operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when searching by reference number with partial matching, but doesn't explicitly state when to use this tool versus the generic 'search' sibling or list operations. No guidance on prerequisites or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
get_watch_detailslist_brandslist_familieslist_watchessearchsearch_refnrMost tools have distinct purposes, but 'search' and 'search_refnr' create ambiguity as both handle reference number searches, with overlapping functionality that could cause misselection. The other tools (get_watch_details, list_brands, list_families, list_watches) are clearly differentiated by their specific resource and action.
All tool names follow a consistent verb_noun pattern with snake_case (e.g., get_watch_details, list_brands, search_refnr). There are no deviations in naming conventions, making the set predictable and readable for an agent.
With 6 tools, this server is well-scoped for its watch database domain. Each tool serves a clear purpose, such as retrieving details, listing categories, or searching, without being overly sparse or bloated, fitting typical expectations for a focused MCP server.
The tool set covers core read operations for watches, brands, and families, including search capabilities, which is appropriate for a database query server. A minor gap exists in the lack of write operations (e.g., create, update, delete), but this may be intentional for a read-only interface, and agents can still perform comprehensive queries.
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