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perplexity-mcp

MCP.Pizza Chef: nachoal

Perplexity-mcp is an MCP server that integrates the Perplexity API to provide real-time web search capabilities for AI assistants like Claude. It delivers comprehensive search results with sources and citations, supports filtering by time periods, and includes a ready-to-use prompt template. This server enables AI models to access up-to-date information from the web securely by loading API keys from environment variables or .env files, enhancing their contextual awareness and response accuracy.

Use This MCP server To

Enable AI assistants to perform real-time web searches Retrieve comprehensive search results with sources and citations Filter search results by time period (day, week, month, year) Integrate web search into AI workflows for up-to-date information Use prompt templates for consistent web search queries Securely manage Perplexity API keys via environment variables

README

Perplexity Web Search MCP Server

A simple MCP (Model Context Protocol) server that provides web search functionality using the Perplexity API. This server allows Claude or other MCP-compatible AI assistants to search the web and get up-to-date information.

Features

  • Search the web with Perplexity's powerful search capabilities
  • Get comprehensive search results with sources and citations
  • Filter results by time period (day, week, month, year)
  • Includes a ready-to-use prompt template for web searches
  • Supports loading API key from environment variables or .env file

Installation

  1. Clone this repository
  2. Install dependencies:
    pip install -e .
    
    or
    uv pip install -e .
    

Configuration

You can set the PERPLEXITY_API_KEY environment variable with your Perplexity API key:

export PERPLEXITY_API_KEY="your-api-key-here"

Alternatively, you can create a .env file in the project root with the following content:

PERPLEXITY_API_KEY=your-api-key-here

A sample .env.example file is provided for reference.

To get a Perplexity API key:

  1. Visit Perplexity API Settings
  2. Create an account if you don't have one
  3. Generate an API key

Usage

Running the server

python server.py

Testing the server

You can test the server functionality without running the full MCP server using the included test script:

python test_server.py "your search query here" --recency month

Options for --recency are: day, week, month (default), year

Using with Claude Desktop

  1. Edit your Claude Desktop configuration file:

    • On macOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
    • On Windows: %APPDATA%/Claude/claude_desktop_config.json
  2. Add the following configuration:

    {
      "perplexity-mcp": {
        "env": {
          "PERPLEXITY_API_KEY": "your-api-key-here"
        },
        "command": "python",
        "args": [
          "/path/to/server.py"
        ]
      }
    }
  3. Restart Claude Desktop

Example Prompts for Claude

  • "Search the web for the latest news about artificial intelligence"
  • "Use Perplexity to find information about climate change published in the past week"
  • "Search for recent research papers on quantum computing from the past month"

API Reference

Tool: search_web(query: str, recency: str = "month") -> str

Search the web using Perplexity API and return results.

Parameters:

  • query: The search query string
  • recency: Filter results by time period - 'day', 'week', 'month' (default), or 'year'

Returns: A comprehensive text response containing:

  1. A detailed summary of the search results
  2. Key facts and information found
  3. Sources with URLs for verification
  4. Any conflicting information if present

Prompt: web_search_prompt(query: str, recency: str = "month") -> str

Creates a prompt template for searching the web with Perplexity.

Parameters:

  • query: The search query
  • recency: Time period filter - 'day', 'week', 'month' (default), or 'year'

Returns: A formatted prompt string that instructs the AI to:

  1. Search for the specified query
  2. Focus on results from the specified time period
  3. Summarize key findings
  4. Highlight important facts
  5. Mention conflicting information
  6. Cite sources with links

License

MIT

perplexity-mcp FAQ

How do I configure the Perplexity API key for this MCP server?
You can set the PERPLEXITY_API_KEY environment variable or create a .env file with the key in the project root.
Can this MCP server filter search results by time period?
Yes, it supports filtering results by day, week, month, or year to refine search relevance.
Is there a prompt template included for web searches?
Yes, the server includes a ready-to-use prompt template to standardize web search queries.
How do I install the perplexity-mcp server?
Clone the repository and install dependencies using 'pip install -e .' or 'uv pip install -e .'.
Can this server be used with multiple AI models?
Yes, it is compatible with any MCP-compatible AI assistant, including Claude, OpenAI, and Gemini.
How does this server enhance AI assistant capabilities?
It provides real-time access to web search results with citations, improving response accuracy and context.
Does the server support secure API key management?
Yes, it supports loading API keys from environment variables or .env files for secure configuration.