What LLM model is used?
The examples connect to Ollama with the Qwen2.5-coder:14b model.
@thrkrdk
基本信息
Model Context Protocol: Client application with Langchain4j for spring boot ai mcp server
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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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