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MCP Server

@Ginga1402

リポジトリ

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

Ginga1402

MCP Server について

Demo of implementation of MCP using Langchain MCP Adapters and Ollama

#mcp#generative-ai#langchain-python#ollama#mcp-server

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": {
    "Model-Context-Protocol-MCP-Demo-with-langchain-MCP-ADAPTERS-Ollama": {
      "command": "python",
      "args": [
        "mathserver.py"
      ]
    }
  }
}

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 an open‑source standard and translator layer that allows large language models (LLMs) to interface with external tools, databases, APIs, and services in a standardized, extensible way.

How to use 🧠 Model Context Protocol (MCP)?

Start MCP servers (e.g., python mathserver.py, python weatherserver.py), then run a client such as client.py (single‑server) or multiclient.py (multi‑server). The client discovers available tools and handles communication between the LLM and the servers.

Key features of 🧠 Model Context Protocol (MCP)

  • Simplified tool integration for LLMs
  • Extended LLM capabilities via external services
  • Scalable, maintainable architecture
  • Standardized communication layer
  • Pre‑built integrations for plug‑and‑play use
  • Flexibility to switch LLM providers and vendors

Use cases of 🧠 Model Context Protocol (MCP)

  • Build an AI assistant that queries databases or APIs
  • Create automated workflows combining email, search, and custom scripts
  • Enable an LLM to perform math operations and fetch live weather data
  • Switch between different LLM providers without rewriting tool integrations

よくある質問

1

How does MCP compare to traditional API integrations?

MCP standardizes how LLMs talk to tools, similar to how REST standardized web services, making integration cleaner, easier, and future‑proof across multiple providers.

2

What runtime or dependencies are required?

The demo uses Python, LangChain, Ollama, and the langchain‑mcp‑adapters library. The protocol itself is language‑agnostic, but the provided examples are Python‑based.

3

Where does my data live when using MCP?

MCP emphasizes best practices for securing your data within your own infrastructure; data flows through your configured servers and services.

4

Are there any known limitations?

The README does not explicitly list limitations. As a new protocol, the ecosystem of pre‑built integrations is growing but may not yet cover all services.

5

How does transport and authentication work?

MCP uses a two‑way transport layer (the MCP Protocol) for secure, structured communication between client and server. Specific authentication methods are not detailed in the README.

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