llms-txt-hub

llms-txt-hub

🤖 The largest directory for AI-ready documentation and tools implementing the proposed llms.txt standard

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The llms.txt hub is a centralized repository for llms.txt implementations and resources, facilitating interactions between LLM-powered tools and services with documentation and codebases. It standardizes documentation access, enhances AI model interpretation, improves AI response accuracy, and sets boundaries for AI content interaction across various projects and platforms.

README:

llmx.txt hub

A comprehensive collection of llms.txt implementations and resources for LLM-powered tools and services.

Screenshot of the llms.txt hub website page

About

The llms.txt file is a standardized way to provide information about how LLM-powered tools and services should interact with your documentation and codebase. This repository serves as a central hub for discovering and sharing llms.txt implementations across different projects and platforms.

Why llms.txt?

The llms.txt standard helps:

  • 🤖 Guide AI models on how to interpret and use your documentation
  • 📚 Standardize documentation access for LLM-powered tools
  • 🔍 Improve accuracy of AI responses about your project
  • 🛠 Enhance developer experience with AI-powered tools
  • 🔒 Set clear boundaries for AI interaction with your content

Categories

Our list is organized into the following categories:

  • 🤖 ai ml: AI and machine learning platforms, tools, and services
  • 📊 data analytics: Data processing, analytics, and visualization tools
  • 💻 developer tools: Development environments, utilities, and productivity tools
  • ☁️ infrastructure cloud: Cloud platforms and infrastructure services
  • ⚡ integration automation: Automation, integration, and workflow platforms
  • 🔒 security identity: Security, authentication, and identity management solutions
  • 🔍 other: Other innovative tools and platforms

LLM Tools and Resources

A curated list of LLM-powered tools and resources with llms.txt implementation.

🤖 ai ml

📊 data analytics

💻 developer tools

☁️ infrastructure cloud

⚡ integration automation

🔒 security identity

Getting Started

Prerequisites

Development

  1. Install dependencies:
# Install pnpm if you haven't already
npm install -g pnpm

# Install project dependencies
pnpm install
  1. Set up your environment variables:
cp .env.example .env.local
  1. Start the development server:
# Start the development server
pnpm dev

The app should now be running at http://localhost:3000

Building for Production

# Build the project
pnpm build

# Start the production server
pnpm start

Useful Commands

# Type checking
pnpm typecheck

# Linting
pnpm lint

# Format code
pnpm format

# Run tests
pnpm test

# Clean up all dependencies and build artifacts
pnpm clean

Adding Your Project

There are three ways to add your project to the list:

Option 1: Web Interface (Recommended)

  1. Visit our website
  2. Log in with your GitHub account (the scope is public_repo, which is required to submit a pull request)
  3. Submit your website through our user-friendly form
  4. Your submission will automatically submit a pull request to this repository and you will get the direct link to your pull request.

Option 2: Using the Generator

  1. Run the generator command:
pnpm generate:website
  1. Follow the prompts to enter your website information:
    • Name of the website/tool
    • Brief description
    • Website URL
    • llms.txt URL
    • Full llms.txt URL (optional)
    • Category (select from available options)
  2. The generator will create an MDX file in the correct location
  3. Submit a pull request with your changes

Option 3: Manual Pull Request

  1. Fork this repository
  2. Create a new MDX file in the /content/websites directory
  3. Ensure your entry includes:
    • Project name, description, website URL, llms.txt URL, and category
  4. Submit a pull request

Both methods will go through our validation process to ensure:

  • Working links to llms.txt files
  • Accurate project descriptions
  • Proper categorization
  • Consistent formatting

Support

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributors

You are welcome to contribute to this project!

Please read our Contributing Guide before submitting a pull request.

Jon Harrell
Jon Harrell

🖋
Andrii Sherman
Andrii Sherman

🖋
_Zaizen_
_Zaizen_

🖋
Alex Atallah
Alex Atallah

🖋

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