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Tavily Web Search MCP Server

by julie-berlin

AI Makerspace: MCP Session Repo for Session 13

This project is a demonstration of the MCP (Model Context Protocol) server, which utilizes the Tavily API for web search capabilities. The server is designed to run in a standard input/output (stdio) transport mode.

Project Overview

The MCP server is set up to handle web search queries using the Tavily API. It is built with the following key components:

  • TavilyClient: A client for interacting with the Tavily API to perform web searches.

Prerequisites

  • Python 3.13 or higher
  • A valid Tavily API key

⚠️NOTE FOR WINDOWS:⚠️

You'll need to install this on the Windows side of your OS.

This will require getting two CLI tool for Powershell, which you can do as follows:

  • winget install astral-sh.uv
  • winget install --id Git.Git -e --source winget

After you have those CLI tools, please open Cursor into Windows.

Then, you can clone the repository using the following command in your Cursor terminal:

git clone https://AI-Maker-Space/AIE7-MCP-Session.git

After that, you can follow from Step 2. below!

Installation

  1. Clone the repository:
    git clone <repository-url> cd <repository-directory>
  2. Configure environment variables: Copy the .env.sample to .env and add your Tavily API key:
    TAVILY_API_KEY=your_api_key_here
  3. 🏗️ Add a new tool to your MCP Server 🏗️

Create a new tool in the server.py file, that's it!

Running the MCP Server

To start the MCP server, you will need to add the following to your MCP Profile in Cursor:

NOTE: To get to your MCP config. you can use the Command Pallete (CMD/CTRL+SHIFT+P) and select "View: Open MCP Settings" and replace the contents with the JSON blob below.

{ "mcpServers": { "mcp-server": { "command" : "uv", "args" : ["--directory", "/PATH/TO/REPOSITORY", "run", "server.py"] } } }

The server will start and listen for commands via standard input/output.

Usage

The server provides a web_search tool that can be used to search the web for information about a given query. This is achieved by calling the web_search function with the desired query string.

Activities:

There are a few activities for this assignment!

🏗️ Activity #1:

Choose an API that you enjoy using - and build an MCP server for it!

✅ Answer:

Built a client that connects with ExchangeRate-API

See code in this repository and screen capture of it working!

🏗️ Activity #2:

Build a simple LangGraph application that interacts with your MCP Server.

You can find details here!

✅ Answer:

See my GitHub Homework Branch for implementation!

-
security - not tested
F
license - not found
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quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables web search capabilities through the Tavily API, allowing users to search the internet for information using natural language queries. Demonstrates MCP server implementation with external API integration.

  1. Prerequisites
    1. ⚠️NOTE FOR WINDOWS:⚠️
      1. Installation
        1. Running the MCP Server
          1. Usage
            1. Activities:
              1. 🏗️ Activity #1:
              2. 🏗️ Activity #2:

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