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mcp-hands-on-with-agentic-ai

by manulthanura·★ 1·Score 31

Educational repository with MCP server examples and templates for building agentic AI capabilities.

ai-llmdeveloper-toolseducation
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Overview

This repository provides a hands-on approach to learning and implementing the Model Context Protocol (MCP). It includes multiple example MCP servers in both Python and TypeScript, demonstrating how to extend AI agents with capabilities like text analysis, weather data retrieval, project documentation, and GitHub model comparison. The repository also contains templates for creating new MCP servers, making it a valuable resource for developers looking to integrate MCP into their applications or build new agentic AI tools.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

you:Learning MCP implementation through practical examples
you:Building custom MCP servers for specific AI agent capabilities
you:Creating tools for text analysis and documentation generation
you:What is the Model Context Protocol (MCP)?
you:What programming languages are supported in this repository?

When to choose this

Choose this repository if you're learning MCP implementation or need examples for building MCP servers with specific functionality like text processing, weather data, or GitHub model comparison.

When NOT to choose this

Don't choose this for production-ready MCP servers or if you need extensive documentation and long-term support beyond educational examples.

Tools this server exposes

9 tools extracted from the README
  • count_characters

    Count the number of characters in a given text

  • count_words

    Count the number of words in a given text

  • get_current_weather

    Get current weather information for a location

  • get_forecasted_weather

    Get forecasted weather information for a location

  • summarize_project

    Summarize a project

  • generate_readme

    Generate a comprehensive README.md document

  • list_github_models

    List all available GitHub Models

  • compare_github_models

    Compare GitHub models

  • run_model_comparison

    Run completion comparisons between models

Note: Tool names were inferred from folder descriptions and README sections. No explicit tool documentation was provided in the main README.

Comparable tools

mcp-server-templatepython-sdktypescript-sdkanthropic-mcp-examples

Installation

Installation

Each example folder contains its own README.md file with specific installation instructions. Generally, the process involves:

  1. Clone the repository to your computer
  2. Navigate to the specific example folder (e.g., mcp-server-examples/text-assist)
  3. Follow the package installation instructions (npm install for TypeScript, pip install for Python)
  4. Run the server in development mode using the MCP Inspector
  5. Configure Claude Desktop or Cursor to use the MCP server

For Claude Desktop, you would typically need to add the server configuration to your claude_desktop_config.json file:

FAQ

What is the Model Context Protocol (MCP)?
MCP is a universal protocol that allows developers to add agent behavior to LLMs by providing context, tools, and instructions consistently.
What programming languages are supported in this repository?
This repository provides examples and templates for both Python and TypeScript MCP servers.

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Last updated · Auto-generated from public README + GitHub signals.