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MCP Python Server & Client

MCP Python Server & Client

A comprehensive implementation of the Model Context Protocol (MCP) in Python, demonstrating all core MCP components including tools, resources, prompts, and transports. This project serves as both a reference implementation and a learning resource for building MCP-based applications.


Table of Contents


Related MCP server: MCP Demo Server

Project Overview

The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). This project implements:

  • MCP Server — Exposes tools (executable functions), resources (data endpoints), and prompts (reusable templates) via the MCP protocol over stdio transport

  • MCP Client — Connects to the server, discovers capabilities, and invokes tools/resources/prompts

  • Full Infrastructure — Configuration management, structured logging, input validation, rate limiting, and comprehensive error handling

Key Features

  • 3 tools: Calculator, String Utilities, Weather (simulated)

  • 4 resources: File Reader (secure), System Info, Platform Info, File Listing

  • 2 prompts: Code Review, Text Summarization

  • Configurable via external YAML with environment variable overrides

  • Log levels (DEBUG/INFO/WARNING/ERROR/CRITICAL) controllable via settings file

  • Security hardening: path traversal prevention, input sanitization, rate limiting

  • 230 automated tests (unit + integration) with pytest


Architecture

The project follows a layered architecture with clear separation of concerns:

┌─────────────────────────────────────────────────────────┐
│                    MCP Client                            │
│  (connects via stdio, calls tools/resources/prompts)    │
└─────────────────────┬───────────────────────────────────┘
                      │ stdio transport
┌─────────────────────▼───────────────────────────────────┐
│                    MCP Server (FastMCP)                  │
├─────────────┬───────────────────┬───────────────────────┤
│   Tools     │    Resources      │      Prompts          │
│ ─────────── │ ───────────────── │ ───────────────────── │
│ Calculator  │ File Reader       │ Code Review           │
│ String Ops  │ System Info       │ Summarization         │
│ Weather     │                   │                       │
├─────────────┴───────────────────┴───────────────────────┤
│              Core Infrastructure                         │
│  Config Loader │ Logger │ Validator │ Rate Limiter      │
├─────────────────────────────────────────────────────────┤
│              Exception Hierarchy                         │
└─────────────────────────────────────────────────────────┘

Project Structure

ai-genai-mcp/
├── config/
│   └── settings.yaml              # All environment-specific configuration
├── src/
│   ├── __init__.py                # Package root
│   ├── config/
│   │   ├── __init__.py
│   │   └── config_loader.py       # YAML loading + Pydantic validation + env overrides
│   ├── utils/
│   │   ├── __init__.py
│   │   ├── exceptions.py          # Custom exception hierarchy (7 types)
│   │   ├── logger.py              # Rotating file + console logging with sanitization
│   │   ├── validator.py           # Input validation and security sanitization
│   │   └── rate_limiter.py        # Token bucket rate limiter
│   ├── server/
│   │   ├── __init__.py
│   │   ├── main.py                # Server entry point and assembly
│   │   ├── tools/
│   │   │   ├── __init__.py
│   │   │   ├── calculator.py      # Math operations tool
│   │   │   ├── string_utils.py    # Text manipulation tool
│   │   │   └── weather.py         # Simulated weather API tool
│   │   ├── resources/
│   │   │   ├── __init__.py
│   │   │   ├── file_reader.py     # Secure file reading resource
│   │   │   └── system_info.py     # System metrics resource
│   │   └── prompts/
│   │       ├── __init__.py
│   │       ├── code_review.py     # Code review prompt template
│   │       └── summarization.py   # Text summarization prompt template
│   └── client/
│       ├── __init__.py
│       ├── main.py                # Client entry point
│       ├── mcp_client.py          # High-level client wrapper
│       └── interactive_demo.py    # Feature demonstration runner
├── tests/
│   ├── conftest.py                # Shared test fixtures
│   ├── unit/                      # 223 unit tests
│   │   ├── test_calculator.py
│   │   ├── test_string_utils.py
│   │   ├── test_weather.py
│   │   ├── test_file_reader.py
│   │   ├── test_system_info.py
│   │   ├── test_code_review_prompt.py
│   │   ├── test_summarization_prompt.py
│   │   ├── test_config_loader.py
│   │   ├── test_logger.py
│   │   ├── test_validator.py
│   │   ├── test_rate_limiter.py
│   │   └── test_exceptions.py
│   └── integration/               # 7 integration tests
│       └── test_client_server.py
├── pyproject.toml                 # Project metadata and dependencies
├── requirements.txt               # Production dependencies
├── requirements-dev.txt           # Development dependencies
├── .gitignore                     # Git ignore patterns
└── README.md                      # This file

Dependencies

Package

Version

Purpose

mcp

>=1.27.2

Official MCP SDK (server + client + transports)

pyyaml

>=6.0.2

YAML configuration file parsing

pydantic

>=2.7.0

Configuration validation and type safety

pytest

>=8.2.0

Testing framework (dev)

pytest-asyncio

>=0.23.0

Async test support (dev)

pytest-cov

>=5.0.0

Test coverage reporting (dev)

ruff

>=0.4.0

Linting and formatting (dev)


Deployment

Prerequisites

  • Python 3.10 or higher

  • pip package manager

  • git (for cloning the repository)

Verify your Python version:

python --version  # Must be 3.10+

Installation

  1. Clone the repository:

git clone <repository-url>
cd ai-genai-mcp
  1. Create a virtual environment (recommended):

python -m venv .venv
source .venv/bin/activate  # Linux/Mac
.venv\Scripts\activate     # Windows
  1. Install the package with dependencies:

# Production only
pip install -e .

# With development tools (testing, linting)
pip install -e ".[dev]"

Running the Server

Start the MCP server using stdio transport (default):

# Using the installed entry point
mcp-server

# Or using Python module syntax
python -m src.server.main

# With custom config file
python -m src.server.main --config /path/to/settings.yaml

The server will listen on stdio and is ready to accept MCP client connections.

Running the Client

The client connects to the server via stdio and runs an interactive demo:

# Using the installed entry point
mcp-client

# Or using Python module syntax
python -m src.client.main

# With custom config file
python -m src.client.main --config /path/to/settings.yaml

Running Tests

# Run all tests
python -m pytest

# Run only unit tests
python -m pytest tests/unit/ -v

# Run only integration tests
python -m pytest tests/integration/ -v

# Run with coverage report
python -m pytest tests/unit/ --cov=src --cov-report=term-missing

# Run linting
ruff check src/ tests/

External Configuration

Settings File

All environment-specific configuration is in config/settings.yaml. This is the single source of truth for runtime behavior. Key sections:

Section

Purpose

server

Host, port, name, transport, timeouts

client

Server URL, retries, timeouts

logging

Level, file path, rotation, format

security

Rate limits, payload limits, CORS origins

tools

Calculator precision, API URLs/keys, string limits

resources

Base directory, file size limits, allowed extensions

Environment Variable Overrides

Any YAML setting can be overridden via environment variables using the convention:

MCP_<SECTION>_<KEY>=value

Examples:

# Override log level
export MCP_LOGGING_LEVEL=DEBUG

# Override server port
export MCP_SERVER_PORT=9090

# Override rate limit
export MCP_SECURITY_RATE_LIMIT_PER_MINUTE=120

# Set weather API key (secrets should always use env vars)
export MCP_TOOLS_WEATHER_API_KEY=your-real-key-here

Environment variables take precedence over YAML file values.

Logging Configuration

Log levels are controlled via config/settings.yaml under the logging section:

logging:
  level: "INFO"          # DEBUG, INFO, WARNING, ERROR, CRITICAL
  file_path: "logs/mcp_application.log"
  max_file_size_bytes: 10485760  # 10 MB rotation
  backup_count: 5        # Keep 5 rotated files
  console_output: true   # Also print to stderr

Or override at runtime:

MCP_LOGGING_LEVEL=DEBUG python -m src.server.main

Log output is automatically sanitized — passwords, API keys, tokens, and secrets are replaced with [REDACTED] in log files.


End-to-End Flow Diagram

sequenceDiagram
    participant Client as MCP Client
    participant Transport as Stdio Transport
    participant Server as MCP Server
    participant Tools as Tool Handlers
    participant Resources as Resource Handlers
    participant Prompts as Prompt Handlers
    participant Config as Config Loader
    participant Validator as Input Validator
    participant RateLimiter as Rate Limiter

    Note over Config: Application Startup
    Config->>Config: Load settings.yaml
    Config->>Config: Apply env var overrides
    Config->>Config: Validate with Pydantic

    Note over Server: Server Initialization
    Server->>Config: Get server config
    Server->>Tools: Register calculator, string, weather
    Server->>Resources: Register file reader, system info
    Server->>Prompts: Register code review, summarization

    Note over Client,Server: Client Connection
    Client->>Transport: Connect via stdio
    Transport->>Server: Initialize protocol
    Server-->>Client: Server capabilities

    Note over Client,Tools: Tool Invocation
    Client->>Server: call_tool("calculate", {op: "add", a: 5, b: 3})
    Server->>RateLimiter: Check rate limit
    RateLimiter-->>Server: Allowed
    Server->>Validator: Validate inputs
    Validator-->>Server: Valid
    Server->>Tools: Execute calculator.add(5, 3)
    Tools-->>Server: Result: 8.0
    Server-->>Client: "Result: 8.0"

    Note over Client,Resources: Resource Reading
    Client->>Server: read_resource("system://info")
    Server->>Resources: Get system information
    Resources-->>Server: JSON system data
    Server-->>Client: System info JSON

    Note over Client,Prompts: Prompt Retrieval
    Client->>Server: get_prompt("code_review", {code: "...", language: "python"})
    Server->>Validator: Validate code input
    Validator-->>Server: Valid
    Server->>Prompts: Build prompt messages
    Prompts-->>Server: [system_msg, user_msg]
    Server-->>Client: Structured prompt messages

Components Reference

Tools

Tool

Operation

Description

calculate

add

Add two numbers

calculate

subtract

Subtract second from first

calculate

multiply

Multiply two numbers

calculate

divide

Divide first by second (guards against /0)

calculate

power

Raise base to exponent

calculate

sqrt

Square root (non-negative only)

calculate

modulo

Remainder of division

string_operation

reverse

Reverse character order

string_operation

count_words

Count words in text

string_operation

uppercase

Convert to uppercase

string_operation

lowercase

Convert to lowercase

string_operation

title_case

Capitalize first letters

string_operation

count_chars

Count letters, digits, spaces

string_operation

replace

Replace substring (extra: "old|new")

string_operation

truncate

Truncate to length with suffix

get_weather

current

Get current weather for a city

get_weather

forecast

Get 1-7 day forecast

Resources

URI

Description

system://info

Full system info (platform, Python, memory, disk, CPU)

system://platform

OS and platform details only

file://list

List available files in data directory

file://read/{path}

Read a file by relative path (security validated)

Prompts

Name

Arguments

Description

code_review

code, language, focus_areas

Generates a structured code review prompt

summarize_text

text, max_length, style

Generates a text summarization prompt


Security

This implementation includes multiple security layers:

  • Path Traversal Prevention — File paths are resolved and validated against the base directory; ../ sequences and null bytes are blocked

  • Input Sanitization — Control characters and null bytes are stripped from all external input

  • Input Length Limits — Configurable maximum lengths prevent memory exhaustion

  • Rate Limiting — Token bucket algorithm limits requests per client per minute

  • Extension Whitelist — Only configured file extensions can be accessed

  • Payload Size Limits — Maximum request payload size is enforced

  • Log Sanitization — Passwords, API keys, and tokens are automatically redacted in logs

  • No Dynamic Code Execution — No eval(), exec(), or dynamic imports


Contributing

  1. Fork the repository

  2. Create a feature branch (git checkout -b feature/amazing-feature)

  3. Write tests for your changes

  4. Ensure all tests pass (python -m pytest)

  5. Ensure code passes linting (ruff check src/ tests/)

  6. Commit your changes

  7. Push to the branch

  8. Open a Pull Request

A
license - permissive license
-
quality - not tested
C
maintenance

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