AI Agents with Model Context Protocol - Python Code Examples

This repository contains Python code examples for the Coursera course “AI Agents with Model Context Protocol.”

Prerequisites

• Python 3.10+
• pip
• An API key from OpenAI, Anthropic, or Google (set in .env file)

Setup

Each module has its own python-code/ directory. To set up any module:

cd /python-code
pip install -r requirements.txt
cp .env.example .env  # Then add your API key(s)

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Course Structure & Code Mapping

Module 1: Getting Started with Model Context Protocol (MCP) for AI Agents

Module 1 is conceptual introduction — no code exercises.

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Module 2: AI Agent Loops & Model Context Protocol

Code Location: 01-intro-to-mcp-agents/python-code/

Key Files:

Commands:

cd 01-intro-to-mcp-agents/python-code
pip install -r requirements.txt
python server.py              # Start the basic MCP server
python agent.py "question"    # Run the basic agent
python test_server.py         # Test server tools directly

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Module 3: Building AI Agents with Model Context Protocol

Code Location: 01-intro-to-mcp-agents/python-code/

Key Files:

Commands:

cd 01-intro-to-mcp-agents/python-code
python workspace_server.py           # Start workspace-aware server
python workspace_agent.py "question" # Run workspace agent with context discovery

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Module 4: Robust Error Handling Techniques for AI Agents

Code Location: 02-failing-forward/python-code/

Key Files:

Commands:

cd 02-failing-forward/python-code
pip install -r requirements.txt
python expense_server.py           # Start the expense server
python expense_agent.py "request"  # Run the expense agent
python test_failing_forward.py     # Run failing forward tests

Pattern Mapping:

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Module 5: Faster, More Predictable, More Capable AI Agents

Code Location: 03-intelligence-budget/python-code/

Key Files:

Commands:

cd 03-intelligence-budget/python-code
pip install -r requirements.txt
python agent_heavy_server.py   # Start agent-heavy server
python tool_heavy_server.py    # Start tool-heavy server
python hybrid_server.py        # Start hybrid server
python test_all.py             # Run comparison tests

Pattern Mapping:

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Quick Reference: Coursera Item → Code File

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Environment Setup

Create a .env file in each module’s python-code/ directory:

OPENAI_API_KEY=your-openai-key-here
ANTHROPIC_API_KEY=your-anthropic-key-here
GOOGLE_API_KEY=your-google-key-here

You only need to provide the API key(s) for the LLM provider(s) you plan to use.

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Project Structure

code-repo/
├── README.md
├── .gitignore
│
├── 01-intro-to-mcp-agents/
│   └── python-code/
│       ├── server.py              # Module 2: Building Your First MCP Server
│       ├── agent.py               # Module 2: Building Your First MCP AI Agent
│       ├── llm.py                 # LLM integration utilities
│       ├── workspace_server.py    # Module 3: All workspace/context items
│       ├── workspace_agent.py     # Module 3: Workspace-related Guidance
│       ├── server_with_resources.py  # Server with MCP resources
│       ├── agent_with_learning.py    # Agent with active learning
│       ├── test_server.py         # Server testing
│       ├── test_resources.py      # Resource testing
│       ├── requirements.txt       # Python dependencies
│       ├── README.md              # Setup instructions
│       └── workspace/             # Sample workspace with .context.md files
│
├── 02-failing-forward/
│   └── python-code/
│       ├── expense_server.py      # Module 4: All error handling items
│       ├── expense_agent.py       # Agent for expense workflows
│       ├── test_failing_forward.py # Pattern tests
│       ├── requirements.txt       # Python dependencies
│       └── README.md              # Setup instructions
│
└── 03-intelligence-budget/
    └── python-code/
        ├── agent_heavy_server.py           # Module 5: Managing Cognitive Load
        ├── tool_heavy_server.py            # Module 5: Managing Cognitive Load
        ├── hybrid_server.py                # Balanced approach
        ├── scripted_orchestration_server.py # Module 5: Scripted Orchestration
        ├── self_prompting_server.py        # Module 5: Self-Prompting
        ├── validate_at_source_server.py    # Module 5: Tool Design for Errors
        ├── database.py                     # Shared mock database
        ├── test_all.py                     # Comparison tests
        ├── requirements.txt                # Python dependencies
        └── README.md                       # Setup instructions

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License

MIT