Skip to main content
Glama
enesjakozh
letsbuildagent

Perplexity Tool for Claude Desktop

by letsbuildagent
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Local

Claude Desktop용 Perplexity 도구

Perplexity AI의 API를 Claude Desktop과 통합하는 맞춤형 MCP 도구를 사용하면 Claude가 웹 기반 연구를 수행하고 인용을 통해 답변을 제공할 수 있습니다.

설치 전제 조건

  1. Git 설치:

    • Mac의 경우:

      • 먼저 터미널에 GXP1을 붙여넣어 Homebrew를 설치하세요.

      • 그런 다음 Git을 설치하세요: GXP2

    • Windows의 경우:

      • git-scm.com 에서 Git을 다운로드하세요

      • 설치 프로그램을 실행하세요

  2. Node.js 설치:

    • Mac의 경우:

      brew install node

    • Windows의 경우:

      • nodejs.org 에서 다운로드

      • 설치 프로그램을 실행하세요

  3. 다음을 실행하여 설치를 확인하세요.

git --version
node --version

Related MCP server: Perplexity MCP Server

도구 설치

  1. 저장소를 복제합니다

git clone https://github.com/letsbuildagent/perplexity-tool
cd perplexity-tool

  1. 종속성 설치

npm install

  1. API 키 설정

두 가지 옵션이 있습니다.

옵션 1(빠른 설정):

  • server.js 를 엽니다

  • 다음 줄을 찾으세요:

const PERPLEXITY_API_KEY = "YOUR-API-KEY-HERE";

  • Perplexity API 키로 교체하세요

옵션 2(모범 사례):

  • .env 파일을 만듭니다.

    # On Mac/Linux:
touch .env
open .env

# On Windows:
notepad .env

    또는 텍스트 편집기에서 .env 라는 이름의 새 파일을 만드세요.

  • .env 파일에 API 키를 추가합니다.

    PERPLEXITY_API_KEY=your-api-key-here

  • dotenv 설치:

    npm install dotenv

  • server.js 업데이트:

    import 'dotenv/config'
const PERPLEXITY_API_KEY = process.env.PERPLEXITY_API_KEY;

  1. Claude Desktop 구성

  • ~/Library/Application Support/Claude/claude_desktop_config.json 엽니다.

  • 다음 구성을 추가합니다.

{
  "mcpServers": {
    "perplexity-tool": {
      "command": "node",
      "args": [
        "/full/path/to/perplexity-tool/server.js"
      ]
    }
  }
}

/full/path/to 저장소를 복제한 실제 경로로 바꾸세요.

  1. Claude Desktop을 다시 시작하세요

용법

설치가 완료되면 Claude를 통해 다음과 같은 명령을 사용하여 도구를 사용할 수 있습니다.

  • "Perplexity에 AI의 최근 발전에 대해 물어보세요"

  • "Perplexity를 사용하여 양자 컴퓨팅의 역사를 연구하세요"

  • "지난 한 달 동안의 기후 변화에 대한 정보를 Perplexity에서 검색하세요"

고급 옵션

추가 매개변수를 지정할 수 있습니다.

  • temperature : 반응의 무작위성을 제어합니다(0-2)

  • max_tokens : 응답 길이를 제한합니다.

  • search_domain_filter : 특정 도메인으로 검색을 제한합니다.

  • search_recency_filter : 기간(일/주/월/년)별로 필터링합니다.

문제 해결

  1. Git을 찾을 수 없습니다:

    • Git을 올바르게 설치했는지 확인하세요

    • 터미널을 다시 시작해 보세요

    • Mac에서는 Homebrew가 PATH에 있는지 확인하세요.

  2. Node.js 오류:

    • node --version 으로 Node.js 설치를 확인하세요.

    • Node.js를 다시 설치해보세요

  3. API 키 문제:

    • API 키를 올바르게 복사했는지 확인하세요.

    • .env 파일에 추가 공백이 없는지 확인하세요.

    • 옵션 2를 사용하는 경우 dotenv가 설치되어 있는지 확인하세요.

  4. Claude에 도구가 나타나지 않음:

    • claude_desktop_config.json에서 경로를 확인하세요

    • 경로가 server.js 파일을 가리키는지 확인하세요.

    • Claude Desktop을 다시 시작하세요

    • 콘솔에서 오류 메시지를 확인하세요.

특허

MIT

보안 참고 사항

코드를 공유하거나 공개할 계획이라면:

  • API 키를 Git에 커밋하지 마세요

  • .env 메서드를 사용하세요(옵션 2)

  • .gitignore 파일에 .env를 추가하세요.

Available Tools

1 tool
ask_perplexityC

Ask a question to Perplexity AI

ParametersJSON Schema
NameRequiredDescriptionDefault
questionYesThe question to ask
temperatureNoResponse randomness (0-2)
max_tokensNoMaximum tokens in response
search_domain_filterNoLimit search to specific domains
search_recency_filterNoFilter results by recencymonth

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Ask a question to Perplexity AI,' which implies it's a query tool, but doesn't describe what happens—e.g., whether it performs web searches, generates responses, has rate limits, or requires authentication. This is a significant gap for a tool with multiple parameters and no output schema.

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 a single, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core action, making it easy to scan and understand quickly.

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

Completeness2/5

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

Given the complexity (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the tool returns, how it behaves (e.g., search-based vs. generative), or any constraints. The agent must rely heavily on the schema and tool name, which is insufficient for effective use.

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

Parameters3/5

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

The input schema has 100% description coverage, so parameters like 'question,' 'temperature,' and 'search_recency_filter' are well-documented in the schema. The description adds no additional meaning beyond the schema, such as explaining how parameters interact or typical use cases. This meets the baseline of 3 since the schema does the heavy lifting.

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

Purpose3/5

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

The description 'Ask a question to Perplexity AI' clearly states the action (ask) and target (Perplexity AI), which is adequate. However, it's somewhat vague about what Perplexity AI is or does—it doesn't specify if this is for general queries, research, or something else. With no sibling tools, differentiation isn't needed, but the purpose could be more specific.

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

Usage Guidelines2/5

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—it doesn't mention use cases, prerequisites, or alternatives. With no sibling tools, there's no need to differentiate, but it lacks any context for appropriate usage, leaving the agent to infer based on the tool name alone.

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. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • Addedask_perplexity
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

C2.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'ask_perplexity' has a clearly distinct purpose that cannot be confused with any other tool in this server.

Naming Consistency5/5

The single tool name follows a clear verb_noun pattern ('ask_perplexity'), and with only one tool, there is perfect consistency. No other naming conventions exist to create inconsistency.

Tool Count2/5

A single tool is generally too few for most server purposes, as it provides minimal functionality and limits agent capabilities. For a Perplexity AI integration, one tool might suffice for basic queries, but it feels thin and lacks operations like follow-up questions or context management.

Completeness2/5

The tool surface is severely incomplete for interacting with Perplexity AI. While 'ask_perplexity' covers basic queries, there are significant gaps such as no support for conversation history, context setting, or handling different query types, which will likely cause agent failures in complex tasks.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • Perplexity MCP Server

    RossH121
    A
    license
    A
    quality
    D
    maintenance
    An MCP server that enables Claude to perform web searches using Perplexity's API with intelligent model selection based on query intent and support for domain and recency filtering.
    6
    4
    MIT

  • Perplexity MCP Server

    Rohit-Seelam
    F
    license
    A
    quality
    D
    maintenance
    Integrates Perplexity AI's search-enhanced language models with Claude Desktop, providing three tools with different complexity levels for quick fact-checking, technical analysis, and deep research.
    3
    2
    -

Appeared in Searches

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/letsbuildagent/perplexity-tool'

If you have feedback or need assistance with the MCP directory API, please join our Discord server