Skill Store 33

Perplexity Search

AI-powered web search, research, and reasoning via Perplexity

by parcadei · MIT

The skill

AI-powered web search, research, and reasoning via Perplexity

Perplexity AI Search

Web search with AI-powered answers, deep research, and chain-of-thought reasoning.

When to Use

  • Direct web search for ranked results (no AI synthesis)
  • AI-synthesized research with citations
  • Chain-of-thought reasoning for complex decisions
  • Deep comprehensive research on topics

Models (2025)

Model Purpose
sonar Lightweight search with grounding
sonar-pro Advanced search for complex queries
sonar-reasoning-pro Chain of thought reasoning
sonar-deep-research Expert-level exhaustive research

Usage

Quick question (AI answer)

uv run python scripts/mcp/perplexity_search.py \
    --ask "What is the latest version of Python?"

Direct web search (ranked results, no AI)

uv run python scripts/mcp/perplexity_search.py \
    --search "SQLite graph database patterns" \
    --max-results 5 \
    --recency week

AI-synthesized research

uv run python scripts/mcp/perplexity_search.py \
    --research "compare FastAPI vs Django for microservices"

Chain-of-thought reasoning

uv run python scripts/mcp/perplexity_search.py \
    --reason "should I use Neo4j or SQLite for small graph under 10k nodes?"

Deep comprehensive research

uv run python scripts/mcp/perplexity_search.py \
    --deep "state of AI agent observability 2025"

Parameters

Parameter Description
--ask Quick question with AI answer (sonar)
--search Direct web search - ranked results without AI synthesis
--research AI-synthesized research (sonar-pro)
--reason Chain-of-thought reasoning (sonar-reasoning-pro)
--deep Deep comprehensive research (sonar-deep-research)

Search-specific options

Parameter Description
--max-results N Number of results (1-20, default: 10)
--recency Filter: day, week, month, year
--domains Limit to specific domains

Mode Selection Guide

Need Use Why
Quick fact --ask Fast, lightweight
Find sources --search Raw results, no AI overhead
Synthesized answer --research AI combines multiple sources
Complex decision --reason Chain-of-thought analysis
Comprehensive report --deep Exhaustive multi-source research

Examples

# Find recent sources on a topic
uv run python scripts/mcp/perplexity_search.py \
    --search "OpenTelemetry AI agent tracing" \
    --recency month --max-results 5

# Get AI synthesis
uv run python scripts/mcp/perplexity_search.py \
    --research "best practices for AI agent logging 2025"

# Make a decision
uv run python scripts/mcp/perplexity_search.py \
    --reason "microservices vs monolith for startup MVP"

# Deep dive
uv run python scripts/mcp/perplexity_search.py \
    --deep "comprehensive guide to building feedback loops for autonomous agents"

API Key Required

Requires PERPLEXITY_API_KEY in environment or ~/.claude/.env.

Use this skill

Connect your agent to the Skill Store MCP server and ask for it by ref: parcadei/perplexity-search-67989647161.

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Details

Publisher
parcadei
Category
AI & Agents › Tool & MCP integration
License
MIT
Updated
2026-01-26

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