perplexity

name	perplexity
description	AI-powered web search and reasoning using Perplexity API through the scraper MCP server. Invoked when searching the web with AI synthesis, conducting research with citations, performing complex reasoning tasks, or answering questions requiring real-time information. Provides two tools for different query types.

Perplexity AI Skill

AI-powered web search and reasoning capabilities via the scraper MCP server.

When to Use This Skill

• Searching the web with AI-synthesized answers
• Research tasks requiring multiple sources with citations
• Complex reasoning and multi-step analysis
• Questions about current events or real-time information
• Comparing options or analyzing trade-offs

Available Tools

Tool	Model	Best For
mcp__scraper__perplexity	sonar	General queries, quick searches, factual lookups
mcp__scraper__perplexity_reason	sonar-reasoning-pro	Complex analysis, comparisons, multi-step reasoning

Tool Usage

1. General Web Search

For straightforward queries and information lookup:

mcp__scraper__perplexity(
    messages=[
        {"role": "user", "content": "What are the latest features in Next.js 15?"}
    ],
    model="sonar",
    temperature=0.3,
    max_tokens=4000
)

Response includes:

• content: AI-synthesized answer with citation markers [1], [2], etc.
• citations: Array of source URLs
• model: Model used
• usage: Token statistics

2. Complex Reasoning

For analytical queries requiring deep thinking:

mcp__scraper__perplexity_reason(
    query="Compare React Server Components vs traditional SSR approaches. Consider performance, developer experience, and migration complexity.",
    temperature=0.3,
    max_tokens=4000
)

Use cases:

• Technology comparisons
• Architecture decisions
• Trade-off analysis
• Multi-factor evaluations

Parameters

Parameter	Type	Default	Description
messages	array	required	Conversation history (perplexity only)
query	string	required	Question to reason about (perplexity_reason only)
model	string	"sonar"	"sonar" or "sonar-pro"
temperature	number	0.3	Creativity 0-2 (lower = more focused)
max_tokens	integer	4000	Maximum response length

Conversation Format

The perplexity tool accepts conversation history:

mcp__scraper__perplexity(
    messages=[
        {"role": "system", "content": "You are a technical advisor."},
        {"role": "user", "content": "What database should I use for a real-time chat app?"},
        {"role": "assistant", "content": "For real-time chat, consider..."},
        {"role": "user", "content": "How does Redis compare to PostgreSQL for this use case?"}
    ]
)

Example Use Cases

Technology Research

mcp__scraper__perplexity(
    messages=[
        {"role": "user", "content": "What are the best practices for implementing authentication in Next.js 15 App Router?"}
    ]
)

Current Events

mcp__scraper__perplexity(
    messages=[
        {"role": "user", "content": "What are the latest AI model releases in 2025?"}
    ]
)

Product Comparison

mcp__scraper__perplexity_reason(
    query="Compare Vercel, Netlify, and AWS Amplify for deploying Next.js applications. Consider pricing, features, performance, and developer experience."
)

Architecture Decisions

mcp__scraper__perplexity_reason(
    query="Should I use a monorepo or polyrepo structure for a microservices architecture? Consider team size of 15 developers, 8 services, and CI/CD complexity."
)

Code Pattern Research

mcp__scraper__perplexity(
    messages=[
        {"role": "user", "content": "What is the recommended way to handle form validation in React 19 with server actions?"}
    ]
)

Security Research

mcp__scraper__perplexity_reason(
    query="Analyze the security implications of storing JWT tokens in localStorage vs httpOnly cookies. Consider XSS, CSRF, and token refresh patterns."
)

Best Practices

Choose the Right Tool

• perplexity: Factual queries, lookups, simple questions
• perplexity_reason: Comparisons, trade-offs, complex analysis

Temperature Settings

# Factual accuracy (recommended for most queries)
temperature=0.3

# More creative/exploratory responses
temperature=0.7

# Maximum creativity (use sparingly)
temperature=1.0

Working with Citations

Responses include numbered citations [1], [2], etc. matching URLs in the citations array:

{
    "content": "Next.js 15 introduces several features [1] including improved caching [2]...",
    "citations": [
        "https://nextjs.org/blog/next-15",
        "https://nextjs.org/docs/caching"
    ]
}

Iterative Research

Build on previous answers:

# Initial query
mcp__scraper__perplexity(messages=[
    {"role": "user", "content": "What is Zustand?"}
])

# Follow-up with context
mcp__scraper__perplexity(messages=[
    {"role": "user", "content": "What is Zustand?"},
    {"role": "assistant", "content": "Zustand is a state management library..."},
    {"role": "user", "content": "How does it compare to Redux Toolkit for a medium-sized application?"}
])

Requirements

The Perplexity tools require PERPLEXITY_API_KEY environment variable to be set on the scraper MCP server. Without it, these tools will not be available.