Weather Java SSE Transport MCP Service
Java Model Context Protocol SSE HTTP Server with Jetty
What is Weather Java SSE Transport MCP Service?
Weather Java SSE Transport MCP Service is a Java-based implementation of the Model Context Protocol (MCP) that demonstrates how to build a working end-to-end solution for weather data retrieval using Server-Sent Events (SSE).
How to use Weather Java SSE Transport MCP Service?
To use the service, you need to build and start the Weather MCP Server using Maven, and then install and configure the fast-agent to interact with the server. You can send messages to the server to retrieve weather forecasts for different cities.
Key features of Weather Java SSE Transport MCP Service?
- Demonstrates interaction with multiple MCP servers (local and remote)
- Uses Claude Sonnet 3.7 for LLM capabilities
- Fetches geographical data and weather forecasts based on user input
- Provides a simple setup without heavy dependencies like Spring
Use cases of Weather Java SSE Transport MCP Service?
- Retrieving weather forecasts for multiple cities based on user queries.
- Demonstrating the capabilities of the Model Context Protocol in a practical application.
- Integrating with other MCP servers for enhanced functionality.
FAQ from Weather Java SSE Transport MCP Service?
- Is this service production-ready?
No, this is a demonstration project and not intended for production use.
- What technologies are used in this project?
The project is built using Java and Jetty, and it utilizes the Model Context Protocol.
- How can I contribute to this project?
You can contribute by forking the repository and submitting pull requests with improvements or additional features.
Weather Java SSE Transport MCP Service
A working implementation Model Context Protocol java-sdk. Includes a fast-agent for the MCP Client to interact with the Weather mcp-server.
⚠️This isn't remotely production grade, just demonstrating how to build something working end to end that can leverage multiple MCP Servers both local (Stdio Transport) and remote (HTTP SSE Transport). Also avoids pulling in as much of Spring as possible, for those who don't want it.
In the demo, you'll see the agent:
- The agent uses Claude Sonnet 3.7 throughout for the LLM bits
- The agent calls out to the "fetch" websearch MCP Server tool to look up lat/long for each city I asked for.
- The agent then uses those lat/long values to call the weather MCP Server tool (implemented in this repository). You can see the calls being made in the upper half of the terminal split window.
- The agent summarizes the forecasts and determine which of the 4 cities is the warmest tomorrow.
The agent is figuring out which tools to call from the context of the user's inputted prompts.
build and start Weather MCP Server
mvn clean package
java -jar java -jar mcp-server/target/mcp-server-1.0-SNAPSHOT.jar
install, configure, and start fast-agent
install
pip install uv
uv pip install fast-agent-mcp
uv run agent.py
Configure Claude and OpenAI api keys
cp fastagent.secrets.yaml.TEMPLATE fastagent.secrets.yaml
then add your api keys to that config file.
Note: Weather MCP Server config
Note, in fastagent.config.yaml we've configured the MCP Servers available to the agent,
in this case our server uses the SSE HTTP Transport, this enables
calling remote MCP Servers :).
mcp:
servers:
weather:
transport: "sse"
read_timeout_seconds: 10
url: "http://localhost:8080/sse"
Lower level for testing
Connect to SSE stream
curl -v -H "Accept: text/event-stream" "http://localhost:8080/sse"
Send messages to /mcp/messages (note, include sessionId from SSE)
curl -X POST "http://localhost:8080/mcp/message?sessionId=b64ad193-6bb3-4e2e-b33c-27a23011acb4" -d '{"hi": "mynameis"}' | jq .
Things to check out:
