MCP Server for Google Search
Google 검색용 MCP 서버
Google Custom Search API와 웹페이지 콘텐츠 추출 기능을 사용하여 웹 검색 기능을 제공하는 모델 컨텍스트 프로토콜 서버입니다.
도구
찾다
Google 맞춤 검색 API를 사용하여 웹 검색을 수행합니다.
전체 웹 또는 특정 사이트 검색
결과의 제어 번호(1-10)
제목, 링크 및 스니펫을 사용하여 구조화된 결과를 얻으세요
웹페이지 리더
모든 웹 페이지에서 콘텐츠 추출:
웹 페이지 콘텐츠 가져오기 및 구문 분석
페이지 제목과 본문 추출
스크립트와 스타일을 제거하여 콘텐츠를 정리합니다.
제목, 텍스트 및 URL을 포함한 구조화된 데이터 반환
Related MCP server: MCP Google Custom Search Server
설치
Google API 키 및 검색 엔진 ID 받기
Google Cloud 프로젝트 만들기:
Google Cloud Console 로 이동
새 프로젝트를 만들거나 기존 프로젝트를 선택하세요
프로젝트에 대한 청구를 활성화하세요
사용자 정의 검색 API 활성화:
API 라이브러리 로 이동
"사용자 정의 검색 API"를 검색하세요
"활성화"를 클릭하세요
API 키 받기:
자격 증명 으로 이동
"자격 증명 만들기" > "API 키"를 클릭하세요.
API 키를 복사하세요
(선택 사항) API 키를 사용자 지정 검색 API로만 제한합니다.
사용자 정의 검색 엔진 만들기:
프로그래밍 가능한 검색 엔진 으로 이동
검색하려는 사이트를 입력하세요(일반 웹 검색의 경우 www.google.com을 사용하세요)
"만들기"를 클릭하세요
다음 페이지에서 "사용자 정의"를 클릭하세요.
설정에서 "전체 웹 검색"을 활성화하세요.
검색 엔진 ID(cx)를 복사하세요
클라이언트 구성
Claude Desktop과 함께 사용하려면 Google API 자격 증명으로 서버 구성을 추가하세요.
MacOS의 경우: ~/Library/Application Support/Claude/claude_desktop_config.json Windows의 경우: %APPDATA%/Claude/claude_desktop_config.json
지엑스피1
Available Tools
2 toolsgoogle_searchC
Perform a web search query
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query | |
| num | No | Number of results (1-10) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits such as rate limits, caching, or return format. The agent is left without important context for safe invocation.
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 concise sentence, but it is too minimal. While there is no wasted text, it lacks structure (e.g., separating purpose from usage details).
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 the simple structure (2 parameters, no output schema), the description fails to mention return behavior or result format, leaving the agent unaware of what to expect after invocation.
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 for both parameters, so the schema itself provides the meaning. The description adds no further semantic value beyond restating the schema.
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 'Perform a web search query' clearly indicates the tool's verb and resource, distinguishing it from the sibling 'read_webpage' which reads a specific page.
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?
No guidance on when to use this tool vs. alternatives (e.g., read_webpage) or any prerequisites. The description lacks explicit usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_webpageA
Fetch and extract text content from a webpage
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the webpage to read |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only states basic purpose without mentioning rate limits, authentication, dynamic content handling, or error responses.
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?
Single sentence, front-loaded with action, no unnecessary words. Perfectly concise.
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 tool with one parameter and no output schema, the description is adequate but lacks details on handling of large pages, timeouts, or what 'text content' entails (e.g., stripping HTML).
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 coverage is 100% (single 'url' parameter described), so baseline is 3. The description adds no extra meaning beyond the schema, such as URL format or protocol support.
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?
Description clearly states the action ('Fetch and extract') and the resource ('text content from a webpage'), distinguishing it from sibling tool 'search' which is for querying.
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?
No explicit guidance on when to use this tool versus alternatives. The sibling 'search' suggests a different purpose, but the description does not clarify contexts or exclusions.
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.
2 tool updates
v1.0.0- Added
google_search - Added
read_webpage
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one performs web searches, the other extracts text from a specific URL. There is no overlap or ambiguity.
Both tool names follow the same verb_noun pattern with snake_case (google_search, read_webpage), making them predictable and consistent.
With only two tools, the set is minimal but covers the core search workflow. It avoids unnecessary bloat, though additional search variants could be justified.
The surface covers the basic search-then-read workflow. Missing features like pagination or filtered searches are minor gaps, but the essential path is complete.
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