広告掲載
MCP.so
ログイン

MCP Server

@S1LV3RJ1NX

リポジトリ

基本情報

カテゴリ

その他

トランスポート

stdio

作者

S1LV3RJ1NX

MCP Server について

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

#mcp#model-context-protocol#ai-applications

MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-server-client-demo": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Model Context Protocol (MCP)?

Model Context Protocol (MCP) is a standardized framework that allows developers to connect large language models (LLMs) with external data sources and tools (functions). This repository provides a demo MCP server implementation using streamable HTTP transport, an auto‑tool registry, and a Dockerfile for scalable, production‑ready deployment. It is aimed at developers building AI applications that need to give LLMs access to live data or custom actions.

How to use Model Context Protocol (MCP)?

Install uv (the Astral package manager), then run uv sync to install dependencies. The server can be started locally or inside Docker and deployed to any cloud provider. Tools are registered automatically using the @mcp_tool decorator. A companion MCP client that works with the OpenAI SDK is included in the client/ directory.

Key features of Model Context Protocol (MCP)

  • Stateless MCP server using streamable HTTP transport
  • Auto‑tool registration via @mcp_tool decorator
  • Dockerfile for containerized deployment
  • Can be run locally or in any cloud provider
  • Demo client integrated with OpenAI SDK

Use cases of Model Context Protocol (MCP)

  • Give an LLM access to a live database or API endpoint
  • Build a custom assistant that fetches real‑time information
  • Combine multiple tools into a single, standardized LLM backend

よくある質問

1

What is MCP?

MCP is a protocol that standardizes how LLMs connect with external data sources and tools (functions).

2

How do I set up the server?

Install `uv`, run `uv sync` to install dependencies, then start the server locally or via Docker.

3

Can I deploy the server to the cloud?

Yes. The server is stateless and can be deployed to any cloud provider using the provided Dockerfile.

4

How are tools registered?

Tools are automatically registered with the `@mcp_tool` decorator placed on the tool function.

5

What transport does the server use?

The server uses streamable HTTP transport, suitable for scalable production deployments.

コメント

「その他」の他のコンテンツ

Activepieces

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

23.2K

Awesome Mlops

visenger

A curated list of references for MLOps

14.0K

Yuppsy

Yuppsy MCP: build and publish real estate websites from your AI assistant. Yuppsy lets your AI assistant create live websites for real estate agents and individual property listings. You don't need a designer or any code

Soar Flight Booking MCP

Soar Flight Booking MCP is a remote MCP server available at https://mcp.soar.flights.

Volley.sh

Volley

A good sequence diagram can solve almost any communication problem in engineering. Volley lets your agent write them as plain text, with the real request and response payloads on every arrow. It checks its own syntax wi

広告掲載