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mcp-tavily-search
Advanced tools
MCP server for integrating Tavily search API with LLMs, providing web search, RAG context generation, and QnA capabilities
A Model Context Protocol (MCP) server for integrating Tavily's search API with LLMs. This server provides intelligent web search capabilities optimized for high-quality, factual results, including context generation for RAG applications and direct question answering.
This server requires configuration through your MCP client. Here are examples for different environments:
Add this to your Cline MCP settings:
{
"mcpServers": {
"mcp-tavily-search": {
"command": "npx",
"args": ["-y", "mcp-tavily-search"],
"env": {
"TAVILY_API_KEY": "your-tavily-api-key"
}
}
}
}
For WSL environments, add this to your Claude Desktop configuration:
{
"mcpServers": {
"mcp-tavily-search": {
"command": "wsl.exe",
"args": [
"bash",
"-c",
"source ~/.nvm/nvm.sh && TAVILY_API_KEY=your-tavily-api-key /home/username/.nvm/versions/node/v20.12.1/bin/npx mcp-tavily-search"
]
}
}
}
The server requires the following environment variable:
TAVILY_API_KEY: Your Tavily API key (required)The server implements three MCP tools with configurable parameters:
Search the web using Tavily Search API, optimized for high-quality, factual results.
Parameters:
query (string, required): Search querysearch_depth (string, optional): "basic" (faster) or "advanced"
(more thorough). Defaults to "basic"topic (string, optional): "general" or "news". Defaults to
"general"days (number, optional): Number of days back to search (news topic
only). Defaults to 3time_range (string, optional): Time range for results ('day',
'week', 'month', 'year' or 'd', 'w', 'm', 'y')max_results (number, optional): Maximum number of results.
Defaults to 5include_answer (boolean, optional): Include AI-generated summary.
Defaults to trueinclude_images (boolean, optional): Include related images.
Defaults to falseinclude_image_descriptions (boolean, optional): Include image
descriptions. Defaults to falseinclude_raw_content (boolean, optional): Include raw HTML content.
Defaults to falseinclude_domains (string[], optional): List of trusted domains to
includeexclude_domains (string[], optional): List of domains to excluderesponse_format (string, optional): 'text', 'json', or 'markdown'.
Defaults to 'text'cache_ttl (number, optional): Cache time-to-live in seconds.
Defaults to 3600force_refresh (boolean, optional): Force fresh results ignoring
cache. Defaults to falseGenerate context for RAG applications using Tavily search.
Parameters:
query (string, required): Search query for context generationmax_tokens (number, optional): Maximum length of generated
context. Defaults to 2000search_depth (string, optional): "basic" or "advanced". Defaults
to "advanced"topic (string, optional): "general" or "news". Defaults to
"general"Get direct answers to questions using Tavily search.
Parameters:
query (string, required): Question to be answeredinclude_sources (boolean, optional): Include source citations.
Defaults to truesearch_depth (string, optional): "basic" or "advanced". Defaults
to "advanced"topic (string, optional): "general" or "news". Defaults to
"general"The server supports flexible domain filtering through two optional parameters:
include_domains: Array of trusted domains to include in search
resultsexclude_domains: Array of domains to exclude from search resultsThis allows you to:
Example domain filtering:
{
"include_domains": ["arxiv.org", "science.gov"],
"exclude_domains": ["example.com"]
}
pnpm install
pnpm build
pnpm dev
The project uses changesets for version management. To publish:
pnpm changeset
pnpm changeset version
pnpm release
Contributions are welcome! Please feel free to submit a Pull Request.
MIT License - see the LICENSE file for details.
FAQs
MCP server for integrating Tavily search API with LLMs, providing web search, RAG context generation, and QnA capabilities
We found that mcp-tavily-search demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 0 open source maintainers collaborating on the project.
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