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Native MCP Client Server

@hackerinheels

リポジトリ

基本情報

カテゴリ

生産性

トランスポート

stdio

作者

hackerinheels

Native MCP Client Server について

A native implementation of the MCP (Model Context Protocol) client-server architecture with HTTP Server-Sent Events (SSE) for real-time communication.

Native MCP Client Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

Native MCP Client 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 Native MCP Client Server?

A native implementation of the Machine Conversation Protocol (MCP) using HTTP Server-Sent Events (SSE) for real-time communication between a WebSocket-based host and multiple tool servers. It provides a host, product server, analytics server, and client for building multi-service tool systems.

How to use Native MCP Client Server?

Set up a Python virtual environment, install dependencies (httpx, fastapi, uvicorn, websockets, python-dotenv, requests, PyYAML), and configure .env files for the host and each tool server. Start the tool servers (e.g., python product-server/server_product.py and python analytics-server/server_analytics.py), then run python mcp-host.py. Send messages like "get products" or "show analytics" to interact.

Key features of Native MCP Client Server

  • Tool discovery via HTTP endpoints
  • Real-time tool execution with SSE
  • WebSocket-based client-host communication
  • Support for Ollama and Gemini LLM backends
  • Multiple tool servers (Product and Analytics)
  • Dynamic tool discovery from all configured servers

Use cases of Native MCP Client Server

  • Query product information from a dedicated server via the "get products" command
  • Retrieve analytics data for daily, weekly, or monthly periods using "get analytics"
  • Combine data from multiple tool servers through a single MCP Host
  • Extend the system by adding custom tool servers with new /tools and /run endpoints

よくある質問

1

What runtime dependencies are required?

Python 3 and packages: httpx, fastapi, uvicorn, websockets, python-dotenv, requests, PyYAML. Optionally Ollama or Gemini for the LLM backend.

2

How does the system communicate?

The MCP Host communicates with clients via WebSocket and with tool servers via HTTP using Server-Sent Events (SSE) for real‑time responses.

3

How can I add a new tool server?

Create a server with `/tools` and `/run` endpoints, add its URL and script path to `config.yaml`, and update the

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