Tavily - OpenClaw Skill — OpenClaw Tutorials

Install Command

npx clawhub@latest install tavily

Installation Guide

Check Environment

Make sure Node.js 22+ and OpenClaw are installed. Run openclaw --version in your terminal to verify.

Run Installation

Run the install command above in your terminal. ClawHub will automatically download and install Tavily to the ~/.openclaw/skills/ directory.

Verify Installation

Run openclaw skills list to check your installed skills and confirm Tavily appears in the list.

Configure (Optional)

Follow the configuration instructions in the description below to add skill settings to ~/.config/openclaw/openclaw.json5.

Manual Installation: Copy the Skill folder to ~/.openclaw/skills/ or the skills/ directory in your project root. Make sure the folder contains a SKILL.md file.

Context-aware intelligent search Automatic search result summarization Deep research mode and content extraction

Detailed Description

Tavily is a search engine API designed for AI Agents and RAG applications, capable of understanding query intent and returning filtered and ranked high-quality search results with automatic summarization and content extraction.

Core Features

Intelligent Search (tavily_search): AI-powered web search that automatically understands query context and returns the most relevant results, with configurable search depth (basic/advanced)
Content Extraction (tavily_extract): Extracts core page content from specified URLs, removing noise like ads and navigation, returning clean text
Deep Research: Advanced mode performs deeper searches covering more sources, suitable for research scenarios requiring comprehensive information
Result Filtering: Supports filtering by domain inclusion/exclusion, with configurable result count and raw content inclusion

Configuration

{
  "mcpServers": {
    "tavily": {
      "command": "npx",
      "args": ["-y", "tavily-mcp"],
      "env": {
        "TAVILY_API_KEY": "tvly-your-api-key"  // Get from tavily.com
      }
    }
  }
}

Use Cases

AI Agent real-time search: Add internet search capabilities to chatbots and AI assistants
RAG data augmentation: Search for the latest information to supplement knowledge base content
Automated research: Batch search multiple topics and extract key information
Content generation: Search reference materials to assist in writing articles and reports

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