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MCP Wikipedia Server

by kaman05010

MCP Wikipedia Server

A production-ready Model Context Protocol (MCP) server that provides Wikipedia search and content retrieval tools using FastMCP and Python 3.11.

Python 3.11 MCP License

🚀 Quick Start

# 1. Set up environment (one-time setup) ./setup.sh # 2. Start the server source .venv311/bin/activate cd src/mcp_server && python mcp_server.py # 3. Test with example client python example_client.py

🎯 Features

  • Wikipedia Search: Find articles with intelligent search and get comprehensive summaries

  • Section Listing: Extract all section titles from any Wikipedia article

  • Content Retrieval: Get specific section content with proper formatting

  • MCP Protocol: Full Model Context Protocol compatibility for AI assistant integration

  • FastMCP Framework: Built on the efficient FastMCP library for optimal performance

  • Python 3.11: Modern Python with latest features and performance improvements

📚 Documentation

Document

Description

📖 Complete Guide

Detailed setup, usage, and development instructions

⚡ Quick Reference

Common commands and tool summaries

🔧 Setup Script

Automated environment setup and verification

💡 Example Client

Sample usage and integration examples

🛠️ Available Tools

Tool

Purpose

Example Usage

fetch_wikipedia_info

Search Wikipedia and get article summaries

Search for "Python programming"

list_wikipedia_sections

Get all section titles from an article

List sections of "Machine Learning"

get_section_content

Retrieve specific section content

Get "History" section from "Artificial Intelligence"

🏗️ Project Structure

MCPClientServer/ ├── 📁 src/mcp_server/ # Core server implementation │ ├── mcp_server.py # Main MCP Wikipedia server │ └── mcp_client.py # Example MCP client ├── 📁 tests/ # Comprehensive test suite │ ├── test_server.py # Unit tests (pytest) │ ├── test_integration.py # Integration tests │ ├── test_performance.py # Performance benchmarks │ ├── test_mcp_compliance.py # MCP protocol compliance │ ├── quick_test.py # Fast validation script │ ├── run_tests.py # Unified test runner │ └── README.md # Testing documentation ├── 📁 .venv311/ # Python 3.11 virtual environment ├── 🔧 setup.sh # Automated setup script ├── 💡 example_client.py # Usage examples and demos ├── 📖 GUIDE.md # Complete documentation ├── ⚡ QUICK_REF.md # Quick reference ├── 📄 pytest.ini # Test configuration ├── 📄 requirements-test.txt # Test dependencies └── 📄 pyproject.toml # Project configuration

🚦 Prerequisites

  • macOS (tested on Apple Silicon and Intel)

  • Python 3.11+ (installed via pyenv recommended)

  • Git (for version control)

📦 Installation Options

Option 1: Automated Setup (Recommended)

chmod +x setup.sh ./setup.sh

Option 2: Manual Setup

# Set up Python 3.11 environment pyenv install 3.11.10 pyenv local 3.11.10 # Create and activate virtual environment python -m venv .venv311 source .venv311/bin/activate # Install dependencies pip install --upgrade pip pip install wikipedia mcp fastmcp

🔌 Integration Examples

With Claude Desktop (MCP Client)

{ "mcpServers": { "wikipedia": { "command": "python", "args": ["/path/to/MCPClientServer/src/mcp_server/mcp_server.py"], "env": { "PYTHONPATH": "/path/to/MCPClientServer/.venv311/lib/python3.11/site-packages" } } } }

Direct Python Usage

from mcp_client import WikipediaClient client = WikipediaClient() result = await client.search_wikipedia("Artificial Intelligence") print(result)

🧪 Testing

Quick Testing

# Fast validation (10 seconds) python tests/quick_test.py # Comprehensive test suite (5 minutes) python tests/run_tests.py

Advanced Testing

# Install test dependencies pip install -r requirements-test.txt # Run specific test suites python tests/run_tests.py --unit # Unit tests only python tests/run_tests.py --integration # Integration tests only python tests/run_tests.py --performance # Performance benchmarks python tests/run_tests.py --mcp # MCP compliance tests # Using pytest directly python -m pytest tests/test_server.py -v --cov=src

Test Suite Overview

  • Unit Tests: Individual function and component testing

  • Integration Tests: End-to-end workflow validation

  • Performance Tests: Response time and load benchmarks

  • MCP Compliance: Protocol specification validation

  • 95%+ Code Coverage: Comprehensive test coverage

See tests/README.md for complete testing documentation.

🐛 Troubleshooting

Issue

Solution

ModuleNotFoundError: No module named 'mcp'

Run

pip install mcp fastmcp

in activated environment

Python version issues

Ensure Python 3.11+ with

python --version

Server won't start

Check if port is available, verify dependencies

Wikipedia API errors

Check internet connection, try different search terms

For detailed troubleshooting, see GUIDE.md.

🤝 Contributing

  1. Fork the repository

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

  3. Commit your changes (git commit -m 'Add amazing feature')

  4. Push to the branch (git push origin feature/amazing-feature)

  5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Resources

🌟 Support

If you find this project helpful, please consider giving it a star ⭐ on GitHub!


Made with ❤️ for the MCP community

-
security - not tested
F
license - not found
-
quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A production-ready server that provides Wikipedia search and content retrieval tools through the Model Context Protocol, enabling AI assistants to search for articles, list sections, and retrieve specific content.

  1. 🚀 Quick Start
    1. 🎯 Features
      1. 📚 Documentation
        1. 🛠️ Available Tools
          1. 🏗️ Project Structure
            1. 🚦 Prerequisites
              1. 📦 Installation Options
                1. Option 1: Automated Setup (Recommended)
                2. Option 2: Manual Setup
              2. 🔌 Integration Examples
                1. With Claude Desktop (MCP Client)
                2. Direct Python Usage
              3. 🧪 Testing
                1. Quick Testing
                2. Advanced Testing
                3. Test Suite Overview
              4. 🐛 Troubleshooting
                1. 🤝 Contributing
                  1. 📄 License
                    1. 🔗 Resources
                      1. 🌟 Support

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