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Client Demo

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Streamable HTTP based MCP server and Client demo with auto registry, Dockerfile setup and env.

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About

Streamable HTTP based MCP server and Client demo with auto registry, Dockerfile setup and env.

README

The Model Context Protocol (MCP) is a powerful framework that enables developers to build AI applications with large language models (LLMs) by providing a standardized way to connect models with external data sources and tools.

MCP is nothing but a protocol to connect LLMs with external data sources and tools (functions).

MCP Server

This repository contains the code for setting up a demo MCP server. It contains:

  • A stateless MCP server with streamable HTTP transport for scalable production deployment.
  • Auto tool registry with @mcp_tool decorator.
  • Docker file to containerize the server.
  • Server can be run locally or in docker and deployed to any cloud provider.

Setup

  • Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh
  • Install dependencies
uv sync

MCP Client

This repository contains the code for setting up a demo MCP client with OpenAI SDK. Refer to the client for more details.

Note: For ease of understanding, both server and client are in the same repository, you can easily keep them in separate repositories / projects.

from github.com/S1LV3RJ1NX/mcp-server-client-demo

Installing Client Demo

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/S1LV3RJ1NX/mcp-server-client-demo

FAQ

Is Client Demo MCP free?

Yes, Client Demo MCP is free — one-click install via Unyly at no cost.

Does Client Demo need an API key?

No, Client Demo runs without API keys or environment variables.

Is Client Demo hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Client Demo in Claude Desktop, Claude Code or Cursor?

Open Client Demo on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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