MCP Learning Demo
A hands-on demonstration project that teaches the Model Context Protocol (MCP) through Python code, allowing users to understand how AI models interact with their context through a provider-agent architecture.
README
MCP Hands-On Learning & Demo Guide
This project teaches the core concepts of the Model Context Protocol (MCP) through hands-on Python code.
What is MCP?
MCP (Model Context Protocol) is an open protocol for standardizing how AI models, tools, and agents interact with their context (files, code, resources, etc.).
Project Structure
models.py: MCP data modelsprovider.py: FastAPI MCP provideragent.py: MCP agent scripttest_mcp.py: Example testsrequirements.txt: Python dependencies
Quickstart for New Users
1. Clone or Download This Repository
2. Set Up Python Environment
Open a terminal in the mcp directory and run:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
3. Start the MCP Provider
In the same terminal, run:
uvicorn provider:app --reload
This starts the FastAPI MCP provider at http://localhost:8000.
4. Run the MCP Agent
Open a new terminal, activate the environment, and run:
source venv/bin/activate
python agent.py
You should see provider info, context items, and a read action result.
5. Run the Tests (Optional)
pytest test_mcp.py
How It Works
- The provider exposes context and actions via a REST API.
- The agent interacts with the provider to perform actions.
- You can extend the provider and agent to add more actions or context types.
For questions or to extend this demo, edit the Python files as needed!
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