lschaffer/qwen3-4b-weathersensorsmcp

Overview

This model, lschaffer/qwen3-4b-weathersensorsmcp, is a 4 billion parameter Qwen3-based language model specifically fine-tuned for weather-focused Model Context Protocol (MCP) tool-calling. Developed by lschaffer using Unsloth, its primary purpose is to act as an expert Cumulus Assistant for DLU, WSCA, and WSC weather sensor data.

Key Capabilities

• Specialized Tool-Calling: Designed for precise interaction with weather sensor data tools, following a strict tool_call: {"name":"<tool_name>","arguments":{...}} format.
• Data Processing Logic: Capable of applying filters, comparisons, and calculations on tool results, including time differences and mapping user terms to channel names.
• Optimized for Weather Workflows: Handles requests for current, historical, and forecast weather data, with specific rules for tool selection based on the query type (e.g., *_by_name tools for known stations).
• Strict Output Formatting: Ensures silent tool calls and concise, factual final answers grounded solely in returned tool data, without extraneous explanations or suggestions.

Good for

• Automated Weather Data Retrieval: Ideal for applications requiring programmatic access and interpretation of weather sensor data.
• Tool-Augmented LLM Agents: Serves as a robust agent for systems that rely on external tools to gather and process specific domain information.
• Integrating with Ollama: Provides a straightforward setup for local deployment and execution using Ollama, including a predefined Modelfile for quick integration.