Modular MCP Server with Python Tools

This project is a test/demo implementation to understand how to build a modular MCP (Model Context Protocol) server in Python, integrate custom tools, and use prompts to interact with language models.

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Purpose

• Explore Python async programming and tool registration with MCP.
• Practice building tools that can be invoked via chat input (e.g., note creation, searching, running commands).
• Experiment with prompt design and using local LLMs (via Ollama) to parse natural language into structured commands.
• Understand how to detect user intents from free text and map them to specific tools.
• Learn how to handle tool invocation responses asynchronously and display results.

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Features

• Tool examples:
  • Note creation and search with SQLite backend.
  • Weather fetching.
  • Mathematical calculation.
  • Time queries.
  • Running shell commands safely.
  • File operations.
• Intent detection via keyword matching and prompt parsing.
• Ollama local LLM integration for structured data extraction.
• Modular design allowing easy addition of new tools.

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Usage

• Start the MCP server (e.g., python simple_modular_server.py).
• Run the client script to chat and interact with tools.
• Use natural language commands like:
  • "make a note. title is shopping list. category groceries."
  • "search note groceries"
  • "run command 'pwd'"
  • "what's the weather in London?"

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Notes

• This project is purely for learning and testing.
• It is not production-ready.
• Designed to help understand MCP architecture, Python tooling, and prompt engineering with local LLMs.

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Requirements

• Python 3.8+
• Ollama installed and running locally with your preferred models (e.g., phi, llama3.2:3b).
• SQLite (built-in with Python).
• Dependencies listed in requirements.txt (if created).

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License

This is an educational project with no license.

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Feel free to experiment and extend!