Wikipedia MCP Server

A comprehensive Model Context Protocol (MCP) server providing access to Wikipedia content with intelligent caching, batch operations, and advanced search capabilities for local development.

Certification

**This MCP server is certified by MCP Review** - your trusted platform for discovering and evaluating Model Context Protocol servers.

Features

Core MCP Tools

• **search** - Enhanced search with snippet control and pagination
• **getPage** - Full page content with configurable sections, images, links, and categories
• **getPageById** - Page retrieval by ID with the same enhancement options
• **getPageSummary** - Fast page summaries via the Wikipedia REST API
• **random** - Random article discovery
• **pageLanguages** - Lists available languages for a given page

Advanced MCP Tools

• **batchSearch** - Search multiple queries simultaneously for efficiency
• **batchGetPages** - Retrieve multiple pages at once with concurrency control
• **searchNearby** - Find Wikipedia articles near specific coordinates
• **getPagesInCategory** - Browse pages within Wikipedia categories

Performance & Reliability

• Intelligent Caching - Memory-based caching for improved performance
• Request Optimization - Endpoint rotation and intelligent routing
• Error Handling - Robust error handling with retry logic
• TypeScript - Fully typed with strict error handling
• Comprehensive Testing - Jest test suite with health validations

Installation

1. Clone or download this repository

2. Install dependencies:

npm install

3. Build the project:

npm run build

Configuration

Add the Wikipedia MCP server to your MCP client configuration:

{
  "mcpServers": {
    "wikipedia": {
      "command": "node",
      "args": ["/path/to/wikipedia-mcp-server/index.js"],
      "env": {
        "CACHE_MAX": "500",
        "CACHE_TTL": "300000",
        "DEFAULT_LANGUAGE": "en",
        "ENABLE_DEDUPLICATION": "true"
      }
    }
  }
}

Note: Replace /path/to/wikipedia-mcp-server with your actual path to the wikipedia-mcp-server directory.

Environment Variables

• CACHE_MAX: Maximum number of items in memory cache (default: 100)
• CACHE_TTL: Cache TTL in milliseconds (default: 300000 = 5 minutes)
• DEFAULT_LANGUAGE: Default Wikipedia language (default: en)
• ENABLE_DEDUPLICATION: Enable request deduplication (default: true)
• USER_AGENT: Custom user agent for Wikipedia API requests

Running Locally

Start the server using npm:

npm start

This starts the MCP server that communicates via stdio, perfect for integration with MCP clients like Cursor.

Available Tools

Core MCP Tools

• **search** - Enhanced search with snippet control and pagination
• **getPage** - Full page content with configurable sections, images, links, and categories
• **getPageById** - Page retrieval by ID with the same enhancement options
• **getPageSummary** - Fast page summaries via the Wikipedia REST API
• **random** - Random article discovery
• **pageLanguages** - Lists available languages for a given page

Advanced MCP Tools

• **batchSearch** - Search multiple queries simultaneously for efficiency
• **batchGetPages** - Retrieve multiple pages at once with concurrency control
• **searchNearby** - Find Wikipedia articles near specific coordinates
• **getPagesInCategory** - Browse pages within Wikipedia categories

Available Resources

Wikipedia MCP Server provides 7 specialized dynamic resources that offer cached Wikipedia data and intelligent content access. These are URI-based resources that can be accessed directly by constructing the appropriate URI pattern.

Note: These resources are dynamic and do not appear in standard resources/list calls. Access them directly using resources/read with the URI patterns below:

wikipedia://article/{title}/{lang}

Returns cached full content of a Wikipedia article with metadata and revision information.

Resource Details:

• Purpose: Access complete article content with local caching
• Benefits: Faster article loading and reduced API calls
• Use Cases: Article reading, content analysis, research workflows

Response Format:

{
  "title": "Artificial Intelligence",
  "lang": "en",
  "content": {
    "pageid": 1164,
    "ns": 0,
    "title": "Artificial Intelligence",
    "revisions": [...],
    "links": [...],
    "categories": [...]
  },
  "cached": false,
  "timestamp": "2025-11-02T17:09:14.866Z"
}

wikipedia://search/cache/{query}

Provides cached search results for Wikipedia queries with snippets and metadata.

Resource Details:

• Purpose: Cache search operations for improved performance
• Benefits: Fast repeated searches and reduced API usage
• Use Cases: Research queries, content discovery, topic exploration

Response Format:

{
  "query": "machine learning",
  "results": [
    {
      "pageid": 233488,
      "title": "Machine learning",
      "snippet": "Machine learning is a method of data analysis that automates analytical model building..."
    }
  ],
  "totalResults": 1500,
  "cached": false,
  "timestamp": "2025-11-02T17:09:14.866Z"
}

wikipedia://metadata/{title}

Offers comprehensive metadata for Wikipedia articles including categories, links, and references.

Resource Details:

• Purpose: Access rich metadata without full article content
• Benefits: Lightweight metadata queries and relationship discovery
• Use Cases: Citation analysis, category exploration, link analysis

Response Format:

{
  "title": "Machine Learning",
  "pageid": 233488,
  "ns": 0,
  "revid": 123456789,
  "lastModified": "2025-11-02T15:30:00Z",
  "categories": [
    { "ns": 14, "title": "Category:Machine learning" }
  ],
  "links": [
    { "ns": 0, "title": "Artificial intelligence" }
  ],
  "references": ["https://doi.org/10.1038/nature14539"],
  "cached": false,
  "timestamp": "2025-11-02T17:09:14.866Z"
}

wikipedia://categories/{title}

Provides category hierarchy and related articles for Wikipedia categories.

Resource Details:

• Purpose: Explore category structures and related content
• Benefits: Topic discovery and content organization
• Use Cases: Topic research, content curation, knowledge organization

Response Format:

{
  "category": "Machine learning",
  "memberCount": 150,
  "members": [
    { "pageid": 123, "ns": 0, "title": "Neural network" }
  ],
  "subcategories": [
    { "pageid": 456, "ns": 14, "title": "Category:Deep learning" }
  ],
  "articles": [
    { "pageid": 789, "ns": 0, "title": "Supervised learning" }
  ],
  "cached": false,
  "timestamp": "2025-11-02T17:09:14.866Z"
}

wikipedia://languages/{title}

Shows available language variants for a Wikipedia article.

Resource Details:

• Purpose: Discover multilingual content availability
• Benefits: Language coverage analysis and translation discovery
• Use Cases: Multilingual research, translation workflows, content localization

Response Format:

{
  "title": "Machine Learning",
  "languageCount": 47,
  "languages": [
    {
      "lang": "es",
      "title": "Aprendizaje automático",
      "url": "https://es.wikipedia.org/wiki/Aprendizaje_automático"
    },
    {
      "lang": "fr",
      "title": "Apprentissage automatique",
      "url": "https://fr.wikipedia.org/wiki/Apprentissage_automatique"
    }
  ],
  "cached": false,
  "timestamp": "2025-11-02T17:09:14.866Z"
}

wikipedia://related/{title}

Lists related articles and see-also links for a Wikipedia article.

Resource Details:

• Purpose: Discover related content and connections
• Benefits: Content discovery and research expansion
• Use Cases: Research expansion, content recommendations, topic exploration

Response Format:

{
  "title": "Machine Learning",
  "seeAlsoLinks": [
    { "ns": 0, "title": "Data mining" },
    { "ns": 0, "title": "Pattern recognition" }
  ],
  "relatedArticles": [
    "Artificial intelligence",
    "Statistics",
    "Computer science"
  ],
  "categories": [
    { "ns": 14, "title": "Category:Machine learning" }
  ],
  "cached": false,
  "timestamp": "2025-11-02T17:09:14.866Z"
}

wikipedia://summary/{title}

Delivers cached summary and key facts for a Wikipedia article.

Resource Details:

• Purpose: Get article essence without full content
• Benefits: Quick information retrieval and content preview
• Use Cases: Content preview, fact-checking, quick reference, research planning

Response Format:

{
  "title": "Machine Learning",
  "summary": "Machine learning is a method of data analysis that automates analytical model building...",
  "keyFacts": {
    "Developed": "1950s",
    "Key figures": ["Arthur Samuel", "Tom Mitchell"],
    "Applications": ["Computer vision", "Natural language processing"]
  },
  "pageid": 233488,
  "lastModified": "2025-11-02T15:30:00Z",
  "wordCount": 1250,
  "cached": false,
  "timestamp": "2025-11-02T17:09:14.866Z"
}

Usage Examples

Once configured in your MCP client (like Cursor), you can use natural language to interact with Wikipedia:

• "Search for articles about artificial intelligence"
• "Get the Wikipedia page for Machine Learning"
• "Find Wikipedia articles near New York City"
• "Show me the summary of Albert Einstein"
• "What languages is the Python programming language article available in?"

Accessing Resources

Resources can be accessed directly using the MCP resources/read method:

{
  "jsonrpc": "2.0",
  "method": "resources/read",
  "params": {
    "uri": "wikipedia://summary/Albert Einstein"
  },
  "id": 1
}

Common Resource URIs:

• wikipedia://summary/{title} - Get article summary
• wikipedia://article/{title}/{lang} - Get full article content
• wikipedia://metadata/{title} - Get article metadata
• wikipedia://languages/{title} - Get available languages
• wikipedia://categories/{title} - Get category information
• wikipedia://related/{title} - Get related articles
• wikipedia://search/cache/{query} - Get cached search results

Testing

The server includes a comprehensive Jest test suite:

npm test

Test Coverage:

• Service instantiation and method availability
• Wikipedia service integration
• Type safety and error handling

License

MIT License - see LICENSE file for details.