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BowenXU0126-aistudio_hw3

BowenXU0126-aistudio_hw3

Remote
github.com/BowenXU0126Developer Tools0Updated 56w ago
Repository

About BowenXU0126-aistudio_hw3

A small MCP server for generating friendly greetings, including an optional pirate-style variation. It is a Smithery CLI-based example project for trying and extending server capabilities.

Key features

  1. 01Personalized greetings
  2. 02Optional pirate style

Use cases

  1. 01Greet someone by name
  2. 02Test an MCP server tool

MCP support

Exposes a greeting tool to MCP clients. The README describes running and interactively testing the server with Smithery CLI.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://server.smithery.ai/@BowenXU0126/aistudio_hw3/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://server.smithery.ai/@BowenXU0126/aistudio_hw3/mcpAuth required

Tools

Details

From the project README

hw3

An MCP server built with Smithery CLI

Prerequisites

Getting Started

  1. Run the server:

    uv run dev

  2. Test interactively:

    uv run playground

Try saying "Say hello to John" to test the example tool.

Development

Your server code is in src/hello_server/server.py. Add or update your server capabilities there.

Deploy

Ready to deploy? Push your code to GitHub and deploy to Smithery:

  1. Create a new repository at github.com/new

  2. Initialize git and push to GitHub:

    git add .
git commit -m "Hello world 👋"
git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.git
git push -u origin main

  3. Deploy your server to Smithery at smithery.ai/new

Comments

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New to MCP?

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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.