If you use an AI coding assistant like GitHub Copilot, Claude, OpenAI Codex, or Cursor, you can connect it directly to kirupa.com using our Model Context Protocol (MCP) Server.
The Model Context Protocol (MCP) is an open standard that lets AI assistants and coding agents plug directly into external knowledge sources and tools. Think of it like a USB-C port for AI tools: instead of relying only on frozen training data or scraping noisy web pages full of navigation menus and scripts, an MCP-aware agent can ask a site's server for structured search results, clean Markdown explanations, and tested code snippets.
The kirupa.com MCP Server exposes over two decades of tutorials, visual explainers, and working code across JavaScript, TypeScript, CSS & Canvas animations, React, and Data Structures & Algorithms as fast, deterministic tools that your AI assistant can call on demand:
search_tutorialsFull-text search (SQLite FTS5 + BM25 ranking) across all 424+ tutorials on kirupa.com, with optional topic section filtering.
query (required), section (optional), limit (1–15)get_tutorialFetches the complete, clean Markdown version of any tutorial—or extracts just the fenced code blocks when code_only: true is passed.
identifier (URL, section/slug, or title), code_only (boolean)find_related_linksFinds related kirupa.com tutorials and canonical Markdown links for any technical concept or existing article URL.
topic_or_url (required), limit (1–15)list_sectionsLists every tutorial category on kirupa.com (Algorithms, Canvas, JavaScript, Animations, React, HTML5, Podcast, and more) with counts and articles.
section (optional), limit (1–100)In addition to those four tools, the server also exposes MCP Resources (including kirupa://llms.txt, kirupa://sections, and kirupa://tutorial/{section}/{slug}) and reusable MCP Prompts (explain_like_kirupa and find_kirupa_tutorial).
Once you add the kirupa.com MCP server to your coding agent, you don't need to manually copy-paste tutorial code into your chat window. Your agent automatically knows how to search and read kirupa.com whenever you ask questions like:
requestAnimationFrame loops work with delta time, and apply that pattern to my canvas animation."Pick your favorite AI coding tool below and copy the configuration snippet:
GitHub Copilot in VS Code / JetBrains: Add the following to your workspace .vscode/mcp.json (or your user MCP settings):
{
"servers": {
"kirupa": {
"type": "http",
"url": "https://www.kirupa.com/mcp/"
}
}
}
Claude Code CLI: Run this single command in your terminal to register the kirupa.com HTTP MCP server:
claude mcp add --transport http kirupa https://www.kirupa.com/mcp/
Or in your project's .mcp.json file:
{
"mcpServers": {
"kirupa": {
"type": "http",
"url": "https://www.kirupa.com/mcp/"
}
}
}
OpenAI Codex CLI: Add the server to your ~/.codex/config.toml file:
[mcp_servers.kirupa] url = "https://www.kirupa.com/mcp/"
Cursor / Windsurf: Add this entry to ~/.cursor/mcp.json (or your project's .cursor/mcp.json):
{
"mcpServers": {
"kirupa": {
"url": "https://www.kirupa.com/mcp/"
}
}
}
Direct JSON-RPC 2.0 Test via curl: Because the server uses standard Streamable HTTP JSON-RPC, you can call it directly from any terminal or script:
curl -s https://www.kirupa.com/mcp/ \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "search_tutorials",
"arguments": { "query": "requestAnimationFrame delta time", "limit": 3 }
}
}'
Want to see what your AI agent sees when it queries the kirupa.com MCP server? Pick a tool and run a real JSON-RPC 2.0 request right from your browser:
Click "Run MCP Tool" above to send a live JSON-RPC 2.0 request to /mcp/.
Just a final word before we wrap up. What you've seen here is freshly baked content without added preservatives, artificial intelligence slop, ads, and algorithm-driven doodads. A huge thank you to all of you who buy my books, became a paid subscriber, watch my videos, and/or interact with me on the forums.
Your support keeps this site going! 😇
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