Perplexity MCP Server
perplexity-mcp MCP 서버
Perplexity AI의 API를 사용하여 웹 검색 기능을 제공하는 모델 컨텍스트 프로토콜(MCP) 서버입니다. Anthropic Claude 데스크톱 클라이언트와 호환됩니다.
예
"지난주 Anthropic에서 무슨 새로운 소식이 있었는지 웹에서 검색해 보세요"와 같은 프롬프트를 사용해 보세요.
Related MCP server: Perplexity MCP Server
글라마 스코어
구성 요소
프롬프트
서버는 단일 프롬프트를 제공합니다.
perplexity_search_web: Perplexity AI를 사용하여 웹 검색
검색 쿼리에 대한 필수 "쿼리" 인수
기간별로 결과를 필터링하기 위한 선택적 "최근성" 인수:
'day': 지난 24시간
'주': 지난 7일
'month': 지난 30일(기본값)
'년': 지난 365일
Perplexity의 API를 사용하여 웹 검색을 수행합니다.
도구
서버는 하나의 도구를 구현합니다.
perplexity_search_web: Perplexity AI를 사용하여 웹 검색
"쿼리"를 필수 문자열 인수로 사용합니다.
결과를 필터링하기 위한 선택적 "최근성" 매개변수(일/주/월/년)
Perplexity API에서 검색 결과를 반환합니다.
설치
Smithery를 통해 설치
Smithery를 통해 Claude Desktop에 Perplexity MCP를 자동으로 설치하려면:
지엑스피1
UV (Fast Python 패키지 및 프로젝트 관리자)가 필요합니다.
uv가 설치되어 있지 않으면
# Using Homebrew on macOS
brew install uv또는
# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows.
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"환경 변수
claude_desktop_config.json 파일에 다음 환경 변수가 필요합니다. Perplexity 에서 API 키를 받을 수 있습니다.
PERPLEXITY_API_KEY: Perplexity AI API 키
선택적 환경 변수:
PERPLEXITY_MODEL: 사용할 Perplexity 모델(지정하지 않으면 기본값은 "sonar")사용 가능한 모델:
sonar-deep-research: 128k 컨텍스트 - 향상된 연구 기능sonar-reasoning-pro: 128k 컨텍스트 - 전문가 중심의 고급 추론sonar-reasoning: 128k 컨텍스트 - 향상된 추론 기능sonar-pro: 200k 컨텍스트 - 전문가급 모델sonar: 128k 컨텍스트 - 기본 모델r1-1776: 128k 컨텍스트 - 대체 아키텍처
업데이트된 모델 목록은 여기에서 확인할 수 있습니다.[ https://docs.perplexity.ai/guides/model-cards ]
커서 및 클로드 데스크톱 설치
Cursor/Claude 구성 파일을 편집하여 이 도구를 mcp 서버로 추가합니다.
"perplexity-mcp": {
"env": {
"PERPLEXITY_API_KEY": "XXXXXXXXXXXXXXXXXXXX",
"PERPLEXITY_MODEL": "sonar"
},
"command": "uvx",
"args": [
"perplexity-mcp"
]
}커서
MacOS의 경우:
/Users/your-username/.cursor/mcp.jsonWindows의 경우:
C:\Users\your-username\.cursor\mcp.json
모든 것이 올바르게 작동한다면 이제 커서에서 도구를 호출할 수 있어야 합니다.
클로드 데스크탑
MacOS의 경우:
~/Library/Application\ Support/Claude/claude_desktop_config.jsonWindows의 경우:
%APPDATA%/Claude/claude_desktop_config.json
서버가 작동하는지 확인하려면 Claude 클라이언트를 열고 "지난주 OpenAI 관련 뉴스를 웹에서 검색해 보세요"와 같은 프롬프트를 사용하세요. 도구 사용을 확인하는 알림 상자가 열립니다. "이 채팅 허용"을 클릭하세요.
Available Tools
1 toolperplexity_search_webC
Search the web using Perplexity AI with recency filtering
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| recency | No | month |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description bears full responsibility for behavioral disclosure. It does not mention whether the operation is read-only, any rate limits, authentication requirements, or side effects. The tool is likely a safe read operation but this is not confirmed, leaving the agent without critical behavioral context.
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 that efficiently conveys the core purpose. No redundant information is present. However, it could be slightly expanded to include more context without losing conciseness, hence a 4 rather than 5.
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 output schema, no annotations, and two parameters with no schema descriptions, the description is severely lacking. It does not specify what the search returns (type of content, structure), any usage limits, or prerequisites. An agent cannot reliably determine if this tool is appropriate for a given task without additional external knowledge.
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 0%, meaning the schema provides no parameter descriptions. The description adds only 'with recency filtering' which hints at the recency parameter but does not explain the query parameter or the meaning of recency enum values (day, week, month, year). This is insufficient for an agent to form correct parameter values without additional knowledge.
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'), the resource ('web'), the specific service ('Perplexity AI'), and includes a key feature ('recency filtering'). This is specific and unambiguous, avoiding tautology by adding value beyond the tool name.
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 is provided on when to use this tool or when to consider alternatives. Since there are no sibling tools, the lack of usage context is less critical, but the description could still mention typical use cases (e.g., 'for up-to-date web results with time constraints'). Currently, it merely rephrases the tool name.
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.
1 tool update
v1.0.0- First observed
perplexity_search_web
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool has a single, clear purpose that cannot be confused with any other tool in the set.
The single tool name follows a consistent verb_noun pattern (perplexity_search_web), and with only one tool, there is no inconsistency to evaluate. The naming is clear and descriptive.
One tool is too few for a server with a broad purpose like web search, as it lacks related operations such as filtering results, getting details, or handling different search types. This minimal set may limit agent functionality in practical scenarios.
The server is severely incomplete for web search functionality, offering only a basic search tool without capabilities like refining queries, paginating results, or accessing cached or specific types of content. This creates significant gaps for agents trying to perform comprehensive web searches.
Maintenance
Related MCP Connectors
Real-time web search, reasoning, and research through Perplexity's API
Enable AI assistants to perform web searches using Perplexity's Sonar Pro.
Hosted Web Crawler MCP server for Claude, ChatGPT and Cursor, with each action switched per account.
Hosted DataForSEO MCP server for Claude, ChatGPT and Cursor, with each action switched per account.
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