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LLM-Optimized Docs

Updated on
Feb 27, 2026

Overview

Quicknode publishes llms.txt indexes across its documentation, guides, and developer resources. These plain-text files follow the llms.txt standard and are designed to help AI tools and LLMs find and reference the right content for any blockchain development task. The indexes cover Quicknode's full content surface: products, pricing, supported chains, marketplace add-ons, RPC methods and API references across all supported networks, development guides, sample applications, courses, and ecosystem resources.

# Fetch the main Quicknode documentation index for LLMs
curl https://www.quicknode.com/docs/llms.txt

Available Indexes

Index
URL
Content
Main platform
Products, chains, and platform resources
Documentation
RPC methods and API references across all supported networks and Quicknode products
Guides
Development guides and tutorials
Sample App Library
Sample applications and code examples
Courses
Blockchain development courses
x402
x402 payment protocol documentation
Builder's Guide
Web3 tool comparisons and ecosystem resources

Open in AI

Quicknode documentation, guides, sample apps, and course pages include a Copy page button that lets you open the current page directly in Claude, ChatGPT, or Perplexity, or copy it as Markdown for use in any LLM.

You can also append .md to any Quicknode content URL to get a clean Markdown version, suitable for pasting into an LLM or using in a RAG pipeline. For example: https://www.quicknode.com/docs/ethereum.md

Usage

Point your AI coding agent or assistant at any index URL to give it access to the relevant documentation surface. For RAG pipelines, each index is plain text and organized by content category, making it straightforward to fetch, chunk, and ingest. The main platform index serves as a discovery layer for routing questions to the appropriate sub-index.


tip

For AI coding agents that need accurate Quicknode product knowledge built in, see Blockchain Skills. To manage your Quicknode infrastructure through a conversational AI interface, see Quicknode MCP.

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