Elite Wiki Knowledge MCP Gateway

Elite Wiki Knowledge MCP Gateway is an MCP server that provides AI assistants with structured access to wiki-based knowledge systems including MediaWiki, Confluence, and other enterprise wiki platforms. This MCP bridge enables language models to search, read, and navigate wiki content, retrieve article revisions, follow internal links, and extract structured knowledge from collaborative documentation systems used by organizations for institutional knowledge management.

When to Use This MCP Server

Connect this server when...

• Your organization maintains a wiki (MediaWiki, Confluence, or similar) for internal documentation and you want AI access to that knowledge base
• You need AI assistants to search and retrieve specific articles, procedures, or reference material from your wiki
• Your workflow involves cross-referencing wiki documentation with other data sources for comprehensive analysis
• You want to keep AI assistants informed about internal processes, policies, and technical documentation stored in wikis
• You need to audit or analyze wiki content coverage, identifying gaps in documentation or outdated articles

Consider alternatives when...

• Your documentation is in Notion, Google Docs, or another platform with its own dedicated MCP server
• You only need public Wikipedia access, which can be handled by general web fetching tools
• Your knowledge base uses a custom CMS rather than a standard wiki platform

Quick Start

Copy
# .mcp.json configuration
{
  "mcpServers": {
    "wiki": {
      "command": "npx",
      "args": ["-y", "@mcp/wiki-knowledge-gateway"],
      "env": {
        "WIKI_URL": "https://wiki.yourcompany.com",
        "WIKI_API_TOKEN": "your-api-token"
      }
    }
  }
}

Connection setup:

1. Identify your wiki platform type (MediaWiki, Confluence, or compatible)
2. Generate an API token or bot account credentials for your wiki
3. Add the configuration above to your .mcp.json file with your wiki URL and credentials
4. Restart your MCP client to connect to your knowledge base

Example tool usage:

# Search for articles
> Search the wiki for articles about the deployment process

# Read a specific page
> Show me the full content of the "Production Runbook" wiki page

# Navigate related content
> What pages link to the "API Authentication" article?

Core Concepts

Concept	Purpose	Details
Wiki Search	Content discovery	Full-text search across wiki articles to find relevant documentation by keyword or topic
Page Retrieval	Content access	Fetching the full rendered content of specific wiki pages including text, tables, and embedded media
Revision History	Change tracking	Access to page edit history showing who changed what and when for audit and version comparison
Category Navigation	Taxonomy browsing	Navigating wiki category trees to discover related articles organized by topic or department
Internal Links	Knowledge graph traversal	Following wiki internal links to explore related content and understand documentation relationships

Architecture:

+------------------+       +------------------+       +------------------+
|  Wiki Platform   |       |  Wiki MCP        |       |  AI Assistant    |
|  MediaWiki/      |<----->|  Gateway (npx)   |<----->|  (Claude, etc.)  |
|  Confluence/etc  | API   |  stdio transport  | stdio |                  |
+------------------+       +------------------+       +------------------+
        |
        v
+------------------------------------------------------+
|  Search > Pages > Revisions > Categories > Links      |
+------------------------------------------------------+

Configuration

Parameter	Type	Default	Description
WIKI_URL	string	(required)	Base URL of your wiki installation (e.g., https://wiki.example.com)
WIKI_API_TOKEN	string	(required)	API token or bot password for authenticated wiki access
wiki_type	string	mediawiki	Wiki platform type: mediawiki, confluence, or auto-detect
default_namespace	string	main	Default wiki namespace for searches and page retrieval
max_results	integer	20	Maximum number of search results returned per query

Best Practices

1. Use search before direct page access. Wiki page titles can be unpredictable. Always search first to find the correct page title rather than guessing URLs. Search catches redirects, alternative titles, and pages in unexpected namespaces.

2. Follow internal links for comprehensive understanding. Wiki articles often reference related pages. When researching a topic, ask the AI to follow key internal links to build a complete understanding rather than relying on a single article.

3. Check revision history for content currency. Before relying on wiki content for critical decisions, check when the page was last updated. Stale wiki articles may contain outdated information. The revision history reveals how actively maintained each article is.

4. Use category navigation for topic discovery. Wiki categories provide a structured taxonomy of content. When you need to understand all documentation related to a topic, browse the relevant categories rather than relying solely on keyword search.

5. Scope access appropriately for your wiki. Some wiki pages may contain sensitive information. Configure the API token with permissions that match the access level appropriate for the AI assistant. Consider using a read-only bot account rather than a personal account.

Common Issues

"Page not found" when accessing articles by title. Wiki page titles are often case-sensitive and may include spaces or special characters. Use the search function to find the correct title rather than constructing titles manually. Some wikis use underscores instead of spaces in URLs.

Search returns too many irrelevant results. Refine search queries with specific terms and use namespace filters to limit results to the relevant section of the wiki. If your wiki supports advanced search syntax, use quoted phrases and boolean operators for precision.

Authentication fails with valid credentials. Different wiki platforms use different authentication mechanisms. MediaWiki uses bot passwords or API tokens, while Confluence uses personal access tokens or OAuth. Verify you are using the correct authentication method for your wiki platform type.