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Perplexity Tool for Claude Desktop

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Herramienta de perplejidad para Claude Desktop

Una herramienta MCP personalizada que integra la API de Perplexity AI con Claude Desktop, lo que permite a Claude realizar investigaciones basadas en la web y proporcionar respuestas con citas.

Requisitos previos de instalación

  1. Instalar Git:

    • Para Mac:

      • Primero instale Homebrew pegando esto en la Terminal: GXP1

      • Luego instala Git: GXP2

    • Para Windows:

  2. Instalar Node.js:

    • Para Mac:

      brew install node

    • Para Windows:

  3. Verifique las instalaciones ejecutando:

git --version
node --version

Related MCP server: Perplexity MCP Server

Instalación de herramientas

  1. Clonar el repositorio

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

  1. Instalar dependencias

npm install

  1. Configura tu clave API

Tienes dos opciones:

Opción 1 (Configuración rápida):

  • Abrir server.js

  • Encuentra esta línea:

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

  • Reemplace con su clave API de Perplexity

Opción 2 (mejor práctica):

  • Crea un archivo .env:

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

# On Windows:
notepad .env

    O simplemente crea un nuevo archivo llamado .env en tu editor de texto

  • Agregue su clave API al archivo .env:

    PERPLEXITY_API_KEY=your-api-key-here

  • Instalar dotenv:

    npm install dotenv

  • Actualizar server.js:

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

  1. Configurar Claude Desktop

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

  • Añade esta configuración:

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

Reemplace /full/path/to con la ruta real donde clonó el repositorio.

  1. Reiniciar Claude Desktop

Uso

Una vez instalada, puedes utilizar la herramienta a través de Claude con comandos como:

  • Pregúntale a Perplexity sobre los últimos avances en IA.

  • Utilizar la Perplejidad para investigar la historia de la computación cuántica.

  • "Buscar información sobre el cambio climático en Perplexity, centrándose en el último mes"

Opciones avanzadas

Puede especificar parámetros adicionales:

  • temperature : controla la aleatoriedad de la respuesta (0-2)

  • max_tokens : limita la longitud de la respuesta

  • search_domain_filter : restringe la búsqueda a dominios específicos

  • search_recency_filter : Filtra por período de tiempo (día/semana/mes/año)

Solución de problemas

  1. Git no encontrado:

    • Asegúrate de haber instalado Git correctamente

    • Intente reiniciar su terminal

    • En Mac, asegúrese de que Homebrew esté en su PATH

  2. Errores de Node.js:

    • Verifique la instalación de Node.js con node --version

    • Intente reinstalar Node.js

  3. Problemas con la clave API:

    • Asegúrate de haber copiado correctamente tu clave API

    • Comprueba que no haya espacios adicionales en tu archivo .env

    • Si usa la Opción 2, verifique que dotenv esté instalado

  4. Herramienta que no aparece en Claude:

    • Verifique la ruta en claude_desktop_config.json

    • Asegúrese de que la ruta apunte a su archivo server.js

    • Reiniciar Claude Desktop

    • Comprueba si hay mensajes de error en la consola.

Licencia

Instituto Tecnológico de Massachusetts (MIT)

Nota de seguridad

Si planeas compartir tu código o hacerlo público:

  • No envíe su clave API a Git

  • Utilice el método .env (Opción 2)

  • Añade .env a tu archivo .gitignore

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.

  1. 1 tool updatev1.0.0
    • Addedask_perplexity
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

C2.9/5.0

Scored across 1 tool

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
ResponsivenessNo issues

Resources

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