What LLM model is used?
The examples connect to Ollama with the Qwen2.5-coder:14b model.
@thrkrdk
基本情報
Model Context Protocol: Client application with Langchain4j for spring boot ai mcp server
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。
It is a Java-based MCP (Model Context Protocol) client/host built with Langchain4j, designed to connect to Spring Boot MCP servers. The server demonstrates integration with private LLMs like Ollama (Qwen2.5-coder:14b) and supports both SSE and STDIO transport modes. It is intended for developers building AI assistants that leverage MCP tools.
The project provides branches with step‑by‑step examples. The final branch (03‑use‑mcp‑server‑stadio) shows the complete setup. You run an MCP server demo image in podman in either SSE or STDIO mode, obtain the server URL (SSE) or STDIO transport, then create a ChatLanguageModel for Ollama, an MCP Transport, an MCP Client, a ToolProvider to fetch tools from the server, and finally an AI services instance (Bot) to call the assistant with a tool.
ChatLanguageModel and AI servicesThe examples connect to Ollama with the Qwen2.5-coder:14b model.
It supports both SSE (Server‑Sent Events) and STDIO (standard input/output) transport modes for MCP servers.
It acts as a **client/host** that connects to external Spring Boot MCP servers.
The setup requires a running Ollama instance and podman to host the MCP server demo image. Optional tools like ngrok/kaggle are used for external URLs in some branches.
The `03-use-mcp-server-stadio` branch is the final branch containing all the code.
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