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Perplexity MCP Server

by jsonallen

Servidor MCP perplexity-mcp

insignia de herrería

Un servidor de Protocolo de Contexto de Modelo (MCP) que proporciona funcionalidad de búsqueda web mediante la API de Perplexity AI . Funciona con el cliente de escritorio Anthropic Claude.

Ejemplo

Le permite utilizar indicaciones como: "Busque en la web para descubrir qué novedades hubo en Anthropic durante la última semana".

Related MCP server: Perplexity MCP Server

Puntuaciones de Glama

Componentes

Indicaciones

El servidor proporciona un único mensaje:

  • perplexity_search_web: Busca en la web usando Perplexity AI

    • Argumento "consulta" obligatorio para la consulta de búsqueda

    • Argumento opcional de "actualidad" para filtrar los resultados por período de tiempo:

      • 'día': últimas 24 horas

      • 'semana': últimos 7 días

      • 'mes': últimos 30 días (predeterminado)

      • 'año': últimos 365 días

    • Utiliza la API de Perplexity para realizar búsquedas web

Herramientas

El servidor implementa una herramienta:

  • perplexity_search_web: Busca en la web usando Perplexity AI

    • Toma "consulta" como un argumento de cadena obligatorio

    • Parámetro opcional de "actualidad" para filtrar resultados (día/semana/mes/año)

    • Devuelve resultados de búsqueda de la API de Perplexity

Instalación

Instalación mediante herrería

Para instalar Perplexity MCP para Claude Desktop automáticamente a través de Smithery :

npx -y @smithery/cli install perplexity-mcp --client claude

Requiere UV (paquete Fast Python y administrador de proyectos)

Si uv no está instalado.

# Using Homebrew on macOS
brew install uv

o

# 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"

Variables de entorno

La siguiente variable de entorno es necesaria en su archivo claude_desktop_config.json. Puede obtener una clave API de Perplexity.

  • PERPLEXITY_API_KEY : Su clave API de Perplexity AI

Variables de entorno opcionales:

  • PERPLEXITY_MODEL : El modelo de perplejidad a utilizar (el valor predeterminado es "sonar" si no se especifica)

    Modelos disponibles:

    • sonar-deep-research : contexto de 128k - Capacidades de investigación mejoradas

    • sonar-reasoning-pro : contexto de 128k: razonamiento avanzado con enfoque profesional

    • sonar-reasoning : contexto de 128k - Capacidades de razonamiento mejoradas

    • sonar-pro : contexto de 200k - Modelo de nivel profesional

    • sonar : contexto 128k - Modelo predeterminado

    • r1-1776 : contexto de 128k - Arquitectura alternativa

Y la lista actualizada de modelos está disponible (aquí) [ https://docs.perplexity.ai/guides/model-cards ]

Instalación de Cursor y Claude Desktop

Agregue esta herramienta como servidor mcp editando el archivo de configuración Cursor/Claude.

  "perplexity-mcp": {
    "env": {
      "PERPLEXITY_API_KEY": "XXXXXXXXXXXXXXXXXXXX",
      "PERPLEXITY_MODEL": "sonar"
    },
    "command": "uvx",
    "args": [
      "perplexity-mcp"
    ]
  }

Cursor

  • En MacOS: /Users/your-username/.cursor/mcp.json

  • En Windows: C:\Users\your-username\.cursor\mcp.json

Si todo funciona correctamente, ahora deberías poder llamar a la herramienta desde Cursor.

Escritorio de Claude

  • En MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

  • En Windows: %APPDATA%/Claude/claude_desktop_config.json

Para verificar el funcionamiento del servidor, abra el cliente de Claude y use una opción como "Buscar noticias sobre OpenAI en la web la semana pasada". Debería aparecer un cuadro de alerta para confirmar el uso de la herramienta. Haga clic en "Permitir este chat".

Available Tools

1 tool
perplexity_search_webC

Search the web using Perplexity AI with recency filtering

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
recencyNomonth

TDQS

C2.9/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness1/5

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.

Parameters2/5

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.

Purpose5/5

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.

Usage Guidelines2/5

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. 1 tool updatev1.0.0
    • First observedperplexity_search_web

TDQS

B3.1/5.0

Scored across 1 tool

Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count2/5

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.

Completeness2/5

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

ActivityInactive
ResponsivenessUnresponsive

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