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MCP server · AI

Practice

by · github.com/Mustafaguzel2/MCP-Practice

A Model Context Protocol (MCP) practice project demonstrating server/client implementation with user management tools, resources, and prompts. Built with TypeScript, Node.js v24, and Google Gemini AI integration.

Unclaimed last commit 6 months ago ai
InstallView source
48Fair

Scored 3 months ago · breakdown

About Practice

Practice is an MCP server published by Mustafaguzel2 in the AI category: a Model Context Protocol (MCP) practice project demonstrating server/client implementation with user management tools, resources, and prompts. Built with TypeScript, Node.js v24, and Google Gemini AI integration. It has been installed 0 times through Conduid.

The repository has 1 stars and 0 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx mcp-practice

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

MCP Practice Project

A Model Context Protocol (MCP) server and client implementation for learning and practicing MCP development. This project demonstrates how to build an MCP server that exposes resources, tools, and prompts, along with an interactive CLI client to interact with them.

Features

MCP Server (src/server.ts):

  • Resources: Query user data via users://all and users://{userId}/profile
  • Tools:
    • create-user - Create a user with explicit fields (name, email, address, phone)
    • create-random-user - Generate a random user using LLM sampling
  • Prompts: generate-fake-user - Generate fake user data based on a name

MCP Client (src/client.ts):

  • Interactive CLI for testing MCP server capabilities
  • Query tools, resources, and prompts
  • Natural language query interface using Google Gemini AI

Tech Stack

  • Runtime: Node.js v24.10.0
  • Language: TypeScript (strict mode, ES modules)
  • Framework: Model Context Protocol SDK (@modelcontextprotocol/sdk)
  • AI: Google Gemini API (@ai-sdk/google)
  • Validation: Zod
  • Storage: JSON file (src/data/users.json)

Quick Start

# Install dependencies
npm install

# Build the server
npm run server:build

# Run the server (for MCP Inspector)
npm run server:inspect

# Run the interactive client
npm run client:dev

Project Structure

src/
  ├── server.ts      # MCP server implementation
  ├── client.ts      # MCP client CLI
  └── data/
      └── users.json # JSON-based user database

Development

This is a practice/learning project for understanding MCP development patterns. The server uses StdioServerTransport for communication, and data is stored in a simple JSON file (not production-ready).

README mirrored from the source repository 3 months ago. The original is authoritative.

Questions

About Practice

How do I install Practice?

Run npx mcp-practice, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Practice safe to use with an AI agent?

Its trust score is 48 out of 100 (fair). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Practice still maintained?

The last commit was 6 months ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.