AI Makerspace: MCP Event

Name: AI Makerspace: MCP Event
Author: AI-Maker-Space

@AI-Maker-Space

Repository

About AI Makerspace: MCP Event

A short demonstration of how you can build your own MCP Server!

#mcp #mcp-server #ai-makerspace

Basic information

Config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is AI Makerspace: MCP Event?

AI Makerspace: MCP Event is a demonstration Model Context Protocol (MCP) server that integrates with the Tavily API to provide web search capabilities. It is designed for developers exploring MCP and works in standard input/output (stdio) transport mode.

How to use AI Makerspace: MCP Event?

Clone the repository, configure the Tavily API key in a .env file, then add the server configuration to your MCP profile (e.g., in Cursor). The server exposes a web_search tool that accepts a query string and returns web search results.

Key features of AI Makerspace: MCP Event

Web search via the Tavily API
Runs as a stdio MCP server
Simple configuration with environment variables
Provides a single web_search tool
Designed for demonstration and learning

Use cases of AI Makerspace: MCP Event

Learning how to build an MCP server
Adding web search to MCP-enabled applications
Testing Tavily API integration within the MCP ecosystem
Demonstrating MCP tool creation and usage

FAQ from AI Makerspace: MCP Event

What does AI Makerspace: MCP Event do?

It is a demonstration MCP server that uses the Tavily API to perform web searches, exposing a web_search tool.

What are the prerequisites to run AI Makerspace: MCP Event?

You need Python 3.13 or higher and a valid Tavily API key.

How do I run AI Makerspace: MCP Event?

Add the server configuration to your MCP profile (e.g., in Cursor) using the uv command with the repository directory and server.py as the entry point.