@jschuller/perplexity-mcp/dist/index.js

MCP server for Perplexity AI — web search with recency filtering, citations, and model control for Claude Desktop and Claude Code

import { Server } from '@modelcontextprotocol/sdk/server/index.js';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
import { CallToolRequestSchema, ListToolsRequestSchema } from '@modelcontextprotocol/sdk/types.js';
import fetch from 'node-fetch';
// Get API key from environment
const apiKey = process.env.PERPLEXITY_API_KEY;
if (!apiKey) {
    process.stderr.write('Error: PERPLEXITY_API_KEY environment variable is required\n');
    process.exit(1);
}
// Default model to use
const defaultModel = process.env.PERPLEXITY_MODEL || 'sonar';
// Create the server instance
const server = new Server({
    name: 'perplexity-mcp',
    version: '2.1.1',
}, {
    capabilities: {
        tools: {},
    },
});
// Define the perplexity_search_web tool
server.setRequestHandler(ListToolsRequestSchema, async () => {
    return {
        tools: [
            {
                name: 'perplexity_search_web',
                description: 'Search the web using Perplexity AI with recency filtering',
                inputSchema: {
                    type: 'object',
                    properties: {
                        query: {
                            type: 'string',
                            description: 'Search query'
                        },
                        recency: {
                            type: 'string',
                            enum: ['day', 'week', 'month', 'year'],
                            default: 'month',
                            description: 'Filter results by recency'
                        },
                        frequency_penalty: {
                            type: 'number',
                            description: 'Multiplicative penalty for new tokens based on their frequency in the text to avoid repetition. Mutually exclusive with the presence_penalty parameter.',
                        },
                        max_tokens: {
                            type: 'integer',
                            description: 'The maximum number of tokens to generate. Sum of max_tokens and prompt tokens should not exceed the model\'s context window limit.',
                        },
                        model: {
                            type: 'string',
                            description: 'The name of the model to use for generating completions. Options include sonar, sonar-pro, and other models listed at https://docs.perplexity.ai/guides/model-cards',
                        },
                        presence_penalty: {
                            type: 'number',
                            description: 'Penalty for new tokens based on their current presence in the text, encouraging topic variety. Mutually exclusive with the frequency_penalty parameter.',
                        },
                        return_citations: {
                            type: 'boolean',
                            description: 'Whether to include citations in the model\'s response.',
                            default: true,
                        },
                        return_images: {
                            type: 'boolean',
                            description: 'Whether to include images in the model\'s response.',
                            default: false,
                        },
                        stream: {
                            type: 'boolean',
                            description: 'Whether to stream the response incrementally using server-sent events.',
                            default: false,
                        },
                        temperature: {
                            type: 'number',
                            description: 'Controls generation randomness, with 0 being deterministic and values approaching 2 being more random.',
                        },
                        top_k: {
                            type: 'integer',
                            description: 'Limits the number of high-probability tokens to consider for generation. Set to 0 to disable.',
                        },
                        top_p: {
                            type: 'number',
                            description: 'Nucleus sampling threshold, controlling the token selection pool based on cumulative probability.',
                        }
                    },
                    required: ['query']
                }
            }
        ]
    };
});
// Handle tool calls
server.setRequestHandler(CallToolRequestSchema, async (request) => {
    if (request.params.name !== 'perplexity_search_web') {
        throw new Error(`Unknown tool: ${request.params.name}`);
    }
    const args = request.params.arguments;
    if (!args || typeof args.query !== 'string') {
        throw new Error('Query is required and must be a string');
    }
    const { query, recency = 'month', frequency_penalty, max_tokens, model = defaultModel, presence_penalty, return_citations = true, return_images = false, stream = false, temperature, top_k, top_p } = args;
    // Construct system message with recency instruction
    let systemContent = "You are a helpful assistant that searches the web to provide accurate, up-to-date information.";
    if (recency) {
        systemContent += ` Focus on results from the last ${recency}.`;
    }
    // Build the messages array
    const messages = [
        {
            role: 'system',
            content: systemContent
        },
        {
            role: 'user',
            content: query
        }
    ];
    // Build API request
    const apiRequest = {
        messages: messages,
        model: model
    };
    // Add optional parameters if provided
    if (frequency_penalty !== undefined)
        apiRequest.frequency_penalty = frequency_penalty;
    if (max_tokens !== undefined)
        apiRequest.max_tokens = max_tokens;
    if (presence_penalty !== undefined)
        apiRequest.presence_penalty = presence_penalty;
    if (return_citations !== undefined)
        apiRequest.return_citations = return_citations;
    if (return_images !== undefined)
        apiRequest.return_images = return_images;
    if (stream !== undefined)
        apiRequest.stream = stream;
    if (temperature !== undefined)
        apiRequest.temperature = temperature;
    if (top_k !== undefined)
        apiRequest.top_k = top_k;
    if (top_p !== undefined)
        apiRequest.top_p = top_p;
    try {
        // Make API call to Perplexity
        const response = await fetch('https://api.perplexity.ai/chat/completions', {
            method: 'POST',
            headers: {
                'Content-Type': 'application/json',
                'Authorization': `Bearer ${apiKey}`
            },
            body: JSON.stringify(apiRequest)
        });
        if (!response.ok) {
            const errorData = await response.text();
            throw new Error(`Perplexity API error: ${response.status} ${response.statusText} - ${errorData}`);
        }
        const result = await response.json();
        // Process and format the response
        const formattedResponse = result.choices[0].message.content;
        return {
            content: [
                {
                    type: 'text',
                    text: formattedResponse
                }
            ],
            meta: {
                model: result.model || model,
                usage: result.usage,
                citations: result.choices[0].message.citations || [],
                images: result.choices[0].message.images || []
            }
        };
    }
    catch (error) {
        throw new Error(`Error in perplexity_search_web: ${error.message}`);
    }
});
// Start the server
const transport = new StdioServerTransport();
server.connect(transport).catch((error) => {
    process.stderr.write(`Server error: ${error}\n`);
    process.exit(1);
});