MCP Hands-On with Agentic AI
This is a code repository for the LinkedIn Learning course Model Context Protocol (MCP): Hands-On with Agentic AI [ASI] [TEXT] [MODELS]
What is MCP Hands-On with Agentic AI?
MCP Hands-On with Agentic AI is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to this is a code repository for the linkedin learning course model context protocol (mcp): hands-on with agentic ai [asi] [text] [models]
This is a code repository for the LinkedIn Learning course Model Context Protocol (MCP): Hands-On with Agentic AI [ASI] [TEXT] [MODELS]
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- This is a code repository for the LinkedIn Learning course M
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx model-context-protocol-mcp-hands-on-with-agentic-ai-2034200Configuration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use MCP Hands-On with Agentic AI
This is the companion code repository for the LinkedIn Learning course "Model Context Protocol (MCP): Hands-On with Agentic AI". It provides four complete, working MCP server examples — a text assistant, a weather server using Open-Meteo, a project documenter, and a GitHub Models comparison tool — plus Python and TypeScript starter templates. Developers use it to learn MCP concepts through hands-on practice, testing each server with Claude Desktop, Cursor, or the MCP Inspector before building their own servers.
Prerequisites
- Node.js 18+ and Python 3.10+ installed on your machine
- An MCP-compatible client such as Claude Desktop or Cursor
- Git installed to clone the repository
- A GitHub account (required for the gh-models-comparison server, which uses GitHub Models API)
- Basic familiarity with TypeScript or Python for customizing the examples
Clone the repository
Clone the LinkedIn Learning course repository to your local machine and navigate into it.
git clone https://github.com/LinkedInLearning/model-context-protocol-mcp-hands-on-with-agentic-ai-2034200.git
cd model-context-protocol-mcp-hands-on-with-agentic-ai-2034200Explore the included example servers
The repo contains four example MCP servers in separate folders: text-assist (Python), open-meteo-weather (Python), projectDocumenter (TypeScript), and gh-models-comparison (TypeScript). Each folder has its own README.md with specific setup instructions.
ls -la
# Folders: text-assist/, open-meteo-weather/, projectDocumenter/, gh-models-comparison/Install dependencies for a Python server
Navigate into any Python server folder (e.g., open-meteo-weather) and install its dependencies using pip or uv.
cd open-meteo-weather
pip install -r requirements.txt
# or with uv:
uv syncInstall dependencies for a TypeScript server
Navigate into any TypeScript server folder (e.g., projectDocumenter) and install its npm dependencies, then build.
cd projectDocumenter
npm install
npm run buildTest with MCP Inspector
Use the MCP Inspector to test any server interactively before connecting it to Claude Desktop or Cursor. This lets you verify tools are exposed correctly.
npx @modelcontextprotocol/inspector python open-meteo-weather/server.py
# or for TypeScript:
npx @modelcontextprotocol/inspector node projectDocumenter/dist/index.jsConfigure Claude Desktop to use a server
Add one of the example servers to your Claude Desktop configuration file. Replace the path with the absolute path on your machine.
Use starter templates to build your own server
The repository includes blank Python and TypeScript MCP starter templates. Copy the relevant template folder to start building your own MCP server following the patterns shown in the course examples.
cp -r python-template/ my-new-server/
cd my-new-server/
# Edit server.py to add your own toolsMCP Hands-On with Agentic AI Examples
Client configuration
Example Claude Desktop configuration for the open-meteo-weather Python server. Adjust the path to match your local clone location.
{
"mcpServers": {
"open-meteo-weather": {
"command": "python",
"args": ["/path/to/model-context-protocol-mcp-hands-on-with-agentic-ai-2034200/open-meteo-weather/server.py"]
},
"projectDocumenter": {
"command": "node",
"args": ["/path/to/model-context-protocol-mcp-hands-on-with-agentic-ai-2034200/projectDocumenter/dist/index.js"]
}
}
}Prompts to try
Example prompts to use once the servers are connected to Claude Desktop or Cursor.
- "What is the current weather in San Francisco?"
- "Give me a 3-day weather forecast for New York City."
- "Count the words and characters in this paragraph: [paste text]"
- "Summarize this project and generate a README for it."
- "List all available GitHub Models and compare GPT-4o with Claude 3.5 Sonnet."Troubleshooting MCP Hands-On with Agentic AI
Server fails to start because Python or Node.js is not found
Ensure the correct runtime is installed and available in your PATH. Use `python --version` or `node --version` to verify. On macOS you may need to use `python3` instead of `python` in the config command.
Tools do not appear in Claude Desktop after adding the config
Restart Claude Desktop completely after editing claude_desktop_config.json. The config file location is ~/Library/Application Support/Claude/claude_desktop_config.json on macOS.
gh-models-comparison server returns authentication errors
This server requires a GitHub Personal Access Token with Models API access. Set the GITHUB_TOKEN environment variable in the env block of your MCP config, or authenticate via the GitHub CLI with `gh auth login`.
Frequently Asked Questions about MCP Hands-On with Agentic AI
What is MCP Hands-On with Agentic AI?
MCP Hands-On with Agentic AI is a Model Context Protocol (MCP) server that this is a code repository for the linkedin learning course model context protocol (mcp): hands-on with agentic ai [asi] [text] [models] It connects AI assistants to external tools and data sources through a standardized interface.
How do I install MCP Hands-On with Agentic AI?
Follow the installation instructions on the MCP Hands-On with Agentic AI GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with MCP Hands-On with Agentic AI?
MCP Hands-On with Agentic AI works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is MCP Hands-On with Agentic AI free to use?
Yes, MCP Hands-On with Agentic AI is open source and available under the NOASSERTION license. You can use it freely in both personal and commercial projects.
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