Use Perplexity to find web sources, get cited research summaries, explore complex decisions, or investigate a topic in depth. Separate modes support quick questions, ranked search results, combined answers, and comprehensive research.
中文简介正在准备中。当前显示英语简介。
AI-powered web search, research, and reasoning via Perplexity
安装前可以查看交给 AI 代理的指令内容。
Web search with AI-powered answers, deep research, and chain-of-thought reasoning.
| 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 |
uv run python scripts/mcp/perplexity_search.py \
--ask "What is the latest version of Python?"
uv run python scripts/mcp/perplexity_search.py \
--search "SQLite graph database patterns" \
--max-results 5 \
--recency week
uv run python scripts/mcp/perplexity_search.py \
--research "compare FastAPI vs Django for microservices"
uv run python scripts/mcp/perplexity_search.py \
--reason "should I use Neo4j or SQLite for small graph under 10k nodes?"
uv run python scripts/mcp/perplexity_search.py \
--deep "state of AI agent observability 2025"
| 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) |
| Parameter | Description |
|---|---|
--max-results N | Number of results (1-20, default: 10) |
--recency | Filter: day, week, month, year |
--domains | Limit to specific domains |
| 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 |
# 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"
Requires PERPLEXITY_API_KEY in environment or ~/.claude/.env.
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Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.
中文简介正在准备中。当前显示英语简介。
Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.
中文简介正在准备中。当前显示英语简介。
Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.
中文简介正在准备中。当前显示英语简介。
Connect Agentica SDK agents to Claude Code CLI through a proxy, an intermediary server. Use setup and debugging guidance to address file permissions, streamed responses, result formatting, and agents reporting success without performing the requested operations.
中文简介正在准备中。当前显示英语简介。
Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.
中文简介正在准备中。当前显示英语简介。
Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.
中文简介正在准备中。当前显示英语简介。