Grokipedia is an encyclopedia and knowledge base service from xAI that provides articles with citations, related content, and verified information. The MCP server enables AI assistants to programmatically search, retrieve, and explore Grokipedia content. Key capabilities include: - Search articles with filters for minimum view counts and sort options by relevance or popularity - Retrieve full article content with smart truncation for lengthy pages - Extract citations and sources to verify information - Discover related pages and explore connections between topics - Extract specific sections from long articles for targeted research - Run guided research workflows for topic investigation, source discovery, and comparative analysis between subjects

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Grokipedia MCP Server

[](https://smithery.ai/server/@skymoore/grokipedia-mcp)

MCP server for searching and retrieving content from Grokipedia

The User of the MCP assumes full responsibility for interacting with Grokipedia.

Please see the Xai Terms of Service if you have any doubts.

Elon, please don't sue me. I only wanted my agents to have access to truthful information and stop referencing wikipedia all the time.

Quick Start

Add this to your MCP configuration file:

{
  "mcpServers": {
    "grokipedia": {
      "command": "uvx",
      "args": ["grokipedia-mcp"]
    }
  }
}

Verifying Installation

You should see the Grokipedia server available with these tools:

And these prompts:

Features

Installation (Development)

Using uv:

cd grokipedia-mcp
uv sync

For development with MCP Inspector and CLI tools:

uv sync --dev

Usage

Run with MCP Inspector (Development)

The fastest way to test and debug (requires dev dependencies):

uv run --dev mcp dev main.py

This launches the MCP Inspector UI where you can:

Run Directly

# Using the installed entry point
uv run grokipedia-mcp
Or as a Python module
uv run python -m grokipedia_mcp
Or directly
uv run python main.py

Available Tools

search

Search for articles in Grokipedia with filtering and sorting options.

Parameters:

Returns: List of search results with title, slug, snippet, relevance score, and view count.

Examples:

// Basic search
{"query": "machine learning", "limit": 5}
// Sort by most viewed
{"query": "python", "sort_by": "views"}
// Filter popular articles only
{"query": "artificial intelligence", "min_views": 1000}

---

get_page

Get complete page information including metadata, content preview, and citations summary. Includes smart suggestion of alternatives if page not found.

Parameters:

Returns: Complete page object with metadata, truncated content, and citation summaries.

Features:

Use this when: You need an overview of a page with metadata and a content preview.

Example:

{"slug": "Machine_learning"}

---

get_page_content

Get only the article content without citations or metadata.

Parameters: