Enables searching Wikipedia articles, extracting section titles, and retrieving specific content from Wikipedia articles with proper formatting
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Wikipedia Serversearch for information about quantum computing"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
๐ 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.pyRelated MCP server: Wikidata MCP Server
๐ฏ 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
๐ Documentation
Document | Description |
Detailed setup, usage, and development instructions | |
Common commands and tool summaries | |
Automated environment setup and verification | |
Sample usage and integration examples |
๐ ๏ธ Available Tools
Tool | Purpose | Example Usage |
| Search Wikipedia and get article summaries | Search for "Python programming" |
| Get all section titles from an article | List sections of "Machine Learning" |
| Retrieve specific section content | Get "History" section from "Artificial Intelligence" |
๐๏ธ Project Structure
MCPClientServer/
โโโ ๐ src/mcp_server/ # Core server implementation
โ โโโ mcp_server.py # Main MCP Wikipedia server
โ โโโ mcp_client.py # Example MCP client
โโโ ๐ tests/ # Comprehensive test suite
โ โโโ test_server.py # Unit tests (pytest)
โ โโโ test_integration.py # Integration tests
โ โโโ test_performance.py # Performance benchmarks
โ โโโ test_mcp_compliance.py # MCP protocol compliance
โ โโโ quick_test.py # Fast validation script
โ โโโ run_tests.py # Unified test runner
โ โโโ README.md # Testing documentation
โโโ ๐ .venv311/ # Python 3.11 virtual environment
โโโ ๐ง setup.sh # Automated setup script
โโโ ๐ก example_client.py # Usage examples and demos
โโโ ๐ GUIDE.md # Complete documentation
โโโ โก QUICK_REF.md # Quick reference
โโโ ๐ pytest.ini # Test configuration
โโโ ๐ requirements-test.txt # Test dependencies
โโโ ๐ pyproject.toml # Project configuration๐ฆ Prerequisites
macOS (tested on Apple Silicon and Intel)
Python 3.11+ (installed via pyenv recommended)
Git (for version control)
๐ฆ Installation Options
Option 1: Automated Setup (Recommended)
chmod +x setup.sh
./setup.shOption 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 fastmcp๐ 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)๐งช Testing
Quick Testing
# Fast validation (10 seconds)
python tests/quick_test.py
# Comprehensive test suite (5 minutes)
python tests/run_tests.pyAdvanced 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=srcTest 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.
๐ Troubleshooting
Issue | Solution |
| Run |
| Ensure Python 3.11+ with |
| Check if port is available, verify dependencies |
| Check internet connection, try different search terms |
For detailed troubleshooting, see GUIDE.md.
๐ค Contributing
Fork the repository
Create a feature branch (
git checkout -b feature/amazing-feature)Commit your changes (
git commit -m 'Add amazing feature')Push to the branch (
git push origin feature/amazing-feature)Open a Pull Request
๐ License
This project is licensed under the MIT License - see the LICENSE file for details.
๐ Resources
๐ Support
If you find this project helpful, please consider giving it a star โญ on GitHub!
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