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Tavily Research

通过脚本调用 Tavily 研究服务,对输入主题进行联网检索与多源综合,支持 mini、pro、auto 三种模型,生成带引用的研究报告,并可将结果保存为 Markdown 文件;认证方式为 OAuth 或 API Key。

evanydl
evanydl
热度 89.24
最近更新 2026-05-11 17:30:11
分类:搜索依赖:代码执行 / MCP 服务 / 第三方 API / 联网浏览搜索 / 读写文件应用场景:研究 / 报告撰写 / 市场分析 / 摘要总结

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add tavily-research
Metadata
name
research
description
Comprehensive research grounded in web data with explicit citations. Use when you need multi-source synthesis—comparisons, current events, market analysis, detailed reports.

Research Skill

Conduct comprehensive research on any topic with automatic source gathering, analysis, and response generation with citations.

Authentication

The script uses OAuth via the Tavily MCP server. No manual setup required - on first run, it will:

  1. Check for existing tokens in ~/.mcp-auth/
  2. If none found, automatically open your browser for OAuth authentication

Note: You must have an existing Tavily account. The OAuth flow only supports login — account creation is not available through this flow. Sign up at tavily.com first if you don't have an account.

Alternative: API Key

If you prefer using an API key, get one at https://tavily.com and add to ~/.claude/settings.json:

{
  "env": {
    "TAVILY_API_KEY": "tvly-your-api-key-here"
  }
}

Quick Start

Tip: Research can take 30-120 seconds. Press Ctrl+B to run in the background.

Using the Script

./scripts/research.sh '<json>' [output_file]

Examples:

# Basic research
./scripts/research.sh '{"input": "quantum computing trends"}'

# With pro model for comprehensive analysis
./scripts/research.sh '{"input": "AI agents comparison", "model": "pro"}'

# Save to file
./scripts/research.sh '{"input": "market analysis for EVs", "model": "pro"}' ./ev-report.md

# Quick targeted research
./scripts/research.sh '{"input": "climate change impacts", "model": "mini"}'

Parameters

Field Type Default Description
input string Required Research topic or question
model string "mini" Model: mini, pro, auto

Model Selection

Rule of thumb: "what does X do?" -> mini. "X vs Y vs Z" or "best way to..." -> pro.

Model Use Case Speed
mini Single topic, targeted research ~30s
pro Comprehensive multi-angle analysis ~60-120s
auto API chooses based on complexity Varies

Examples

Quick Overview

./scripts/research.sh '{"input": "What is retrieval augmented generation?", "model": "mini"}'

Technical Comparison

./scripts/research.sh '{"input": "LangGraph vs CrewAI for multi-agent systems", "model": "pro"}'

Market Research

./scripts/research.sh '{"input": "Fintech startup landscape 2025", "model": "pro"}' fintech-report.md