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Weather Java SSE Transport MCP Service

@stantonk

基本信息

分类

媒体与设计

许可证

MIT

传输方式

stdio

作者

stantonk

关于 Weather Java SSE Transport MCP Service

Java Model Context Protocol SSE HTTP Server with Jetty

Weather Java SSE Transport MCP Service 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块,请前往代码仓库查看安装说明。

代码仓库

Weather Java SSE Transport MCP Service 工具

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。

概览

What is Weather Java SSE Transport MCP Service?

A demonstration implementation of the Model Context Protocol java-sdk that includes a fast-agent for the MCP Client to interact with a Weather MCP server. It shows how to build an end-to-end system leveraging both local (Stdio Transport) and remote (HTTP SSE Transport) MCP servers while avoiding excessive Spring dependencies. Intended for developers learning about MCP server and client integration.

How to use Weather Java SSE Transport MCP Service?

Build the server with mvn clean package then start with java -jar mcp-server/target/mcp-server-1.0-SNAPSHOT.jar. Install the fast-agent using pip install uv, then uv pip install fast-agent-mcp, and run with uv run agent.py. Configure Claude and OpenAI API keys in fastagent.secrets.yaml. The server is configured in fastagent.config.yaml with transport "sse", a 10‑second read timeout, and URL http://localhost:8080/sse.

Key features of Weather Java SSE Transport MCP Service?

  • Implements Model Context Protocol java‑sdk
  • Includes fast-agent for MCP Client interaction
  • Supports local Stdio and remote HTTP SSE transports
  • Avoids pulling in Spring where possible
  • Agent uses Claude Sonnet 3.7 for LLM decisions
  • Agent autonomously selects tools from user prompts

Use cases of Weather Java SSE Transport MCP Service?

  • Developer testing local MCP server interactions with an agent
  • Agent‑based weather data retrieval using geographic tool chaining
  • Demonstrating hybrid MCP server architecture (Stdio + SSE)
  • Evaluating the MCP java‑sdk implementation end‑to‑end
  • Experimenting with tool selection driven by natural language prompts

常见问题

1

What runtime dependencies are required?

Java and Maven for the server, Python with `uv` for the fast-agent, and API keys for Claude and OpenAI (configured in `fastagent.secrets.yaml`).

2

What transport protocols are supported?

The server uses HTTP SSE (Server‑Sent Events) transport. The agent configuration can also connect

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