Web Search MCP Server
@matemiro
About Web Search MCP Server
A Model Context Protocol (MCP) server that provides a web search tool using the Tavily API. This server enables AI models to search the internet and retrieve up-to-date information.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"MCP-Tavily-Web-Search-Server": {
"command": "uv",
"args": [
"venv"
]
}
}
}Tools
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Overview
What is Web Search MCP Server?
Web Search MCP Server is a Model Context Protocol (MCP) server that provides a web search tool using the Tavily API. It acts as a bridge between AI models and the Tavily search engine, enabling models to search the internet and retrieve up-to-date information during conversations.
How to use Web Search MCP Server?
Install Python 3.13+ and uv, then clone the repository, set up a virtual environment, and install dependencies with uv pip sync. Create a .env file from the provided template and add your Tavily API key. Run the server with uv run web_search_server.py. The server uses the stdio transport method for MCP communication.
Key features of Web Search MCP Server
- Real-time web search via Tavily API
- Customizable search topic (general, news, finance)
- Adjustable search depth (basic, advanced)
- Maximum results and time range filtering (day, week, month, year)
- Domain inclusion and exclusion lists
Use cases of Web Search MCP Server
- AI assistants retrieving current internet information during conversations
- Chatbots answering queries that require real-time data
- Research agents gathering up-to-date results from specified domains
- News or finance searches filtered by recent time ranges
FAQ from Web Search MCP Server
What exactly does this server do?
It exposes a single tool (search_web_tool) that lets AI models search the web via the Tavily API and return a list of results containing title, URL, content, and relevance score.
What are the runtime requirements?
Python 3.13+, the uv package installer/resolver, and a valid Tavily API key obtained from tavily.com.
How do I configure the Tavily API key?
Copy the env-sample file to .env, then edit .env to set TAVILY_API_KEY=your-api-key-here.
What parameters does the search tool accept?
It requires a query string and accepts optional parameters: search_topic, search_depth, max_results, time_range, include_domains, and exclude_domains.
How are errors handled?
If an error occurs during a search operation, the tool returns an error message describing the issue.
Frequently asked questions
What exactly does this server do?
It exposes a single tool (`search_web_tool`) that lets AI models search the web via the Tavily API and return a list of results containing title, URL, content, and relevance score.
What are the runtime requirements?
Python 3.13+, the `uv` package installer/resolver, and a valid Tavily API key obtained from [tavily.com](https://tavily.com/).
How do I configure the Tavily API key?
Copy the `env-sample` file to `.env`, then edit `.env` to set `TAVILY_API_KEY=your-api-key-here`.
What parameters does the search tool accept?
It requires a `query` string and accepts optional parameters: `search_topic`, `search_depth`, `max_results`, `time_range`, `include_domains`, and `exclude_domains`.
How are errors handled?
If an error occurs during a search operation, the tool returns an error message describing the issue.
Basic information
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