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MCP (MCP) 서버

@sangminpark9

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基本情報

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トランスポート

stdio

作者

sangminpark9

MCP (MCP) 서버 について

概要はまだありません

#mcp-server#llm#api

MCP (MCP) 서버 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-sangminpark9": {
      "command": "python",
      "args": [
        "setup.py"
      ]
    }
  }
}

MCP (MCP) 서버 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 MCP (Model Context Protocol) 서버?

MCP (Model Context Protocol) 서버 is a service that integrates and manages multiple large language models (DeepSeek and Llama) through a standardized API interface. It provides easy model switching, conversation context management, and supports multiple storage backends. It is designed for developers who need a unified interface to work with different LLMs.

How to use MCP (Model Context Protocol) 서버?

Clone the repository, run python setup.py (optionally with --download-models) to set up the environment, and start the server with uvicorn app.main:app --reload. Docker users can run docker-compose up -d. The main API endpoint is POST /api/chat with a JSON body containing session_id, messages, model, and parameters.

Key features of MCP (Model Context Protocol) 서버

  • Integrates DeepSeek and Llama models
  • Easy model switching and routing
  • Conversation context management
  • Standardized REST API interface
  • Multiple storage backends: memory, Redis, SQLite

Use cases of MCP (Model Context Protocol) 서버

  • Building chatbots that switch between DeepSeek and Llama
  • Text generation with customizable parameters
  • Korean‑language translation and reasoning tasks
  • Development of LLM‑powered applications with persistent session context

よくある質問

1

What Python version is required?

The server requires Python 3.8 or higher.

2

Can I run the server without a GPU?

Yes, a CPU‑only environment is supported, but a CUDA‑compatible GPU is recommended for better performance.

3

Which models are supported?

DeepSeek and Llama models are supported. DeepSeek offers text‑generation, code‑generation, and reasoning; Llama is Korean‑language specialized with translation capabilities.

4

How do I add a new model?

Create a new model class in `app/models` that inherits from `BaseModel`, register it in `app/models/router.py`, and update the routing configuration in `app/core/config.py`.

5

How can I delete a conversation session?

Send a `DELETE /api/sessions/{session_id}` request. The server responds with a success status and message confirming deletion.

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