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Build on 1Password with LLMs

1Password developer documentation is optimized for consumption by large language models (LLMs). Whether you're using an AI coding assistant, building an agent, or working with a chatbot, you can point it to our documentation for accurate, up-to-date context about 1Password developer tools.

Quick start​

Give your LLM one of these URLs depending on what you need:

What you needURLSize
Full index of all docs with descriptions/llms.txt~40 KB
All documentation in a single file/llms-full.txt~1.6 MB
CLI docs only/llms-cli.txt~800 KB
SDK docs only (Python, JS, Go)/llms-sdks.txt~135 KB
SSH & Git docs only/llms-ssh.txt~140 KB
Secrets Automation (Service Accounts, Connect, CI/CD, K8s)/llms-secrets-automation.txt~260 KB
Events API docs only/llms-events-api.txt~130 KB
Any single page as MarkdownAppend .md to the URL of any articleVaries

How it works​

llms.txt​

The /llms.txt file follows the llms.txt standard, providing a structured index of all documentation pages with titles, URLs, and descriptions. This is the best place to start for any LLM. It can scan the index to find relevant pages, then retrieve individual pages as needed.

Per-topic files​

If your LLM has a large enough context window, you can provide a topic-specific file that contains all the documentation for that area. For example, if you're building an integration with 1Password CLI, point your LLM to /llms-cli.txt and it will have the complete CLI documentation — commands, guides, shell plugins, and all reference material — in a single request.

Individual pages as Markdown​

Every documentation page is available as clean Markdown by appending .md to its URL. For example:

This is useful for retrieval-augmented generation (RAG) workflows or when you only need context about a specific topic.

You can also use the Copy page as Markdown button at the top of any page to copy the Markdown content directly to your clipboard and paste it into your LLM conversation.

Using 1Password docs with AI tools​

Cursor, Windsurf, and other AI IDEs​

Most AI coding assistants let you attach documentation context. To use 1Password developer documentation, do one of the following:

  • Paste the URL of a per-topic file (e.g., https://developer.1password.com/llms-sdks.txt) when prompted for context, or include it in your prompt.
  • In Cursor, use the @Docs feature to add https://developer.1password.com/llms.txt as a documentation source.

ChatGPT, Claude, and other chatbots​

When asking an LLM about 1Password developer tools, do one of the following:

  • Copy the relevant per-topic file URL and ask the LLM to read it.
  • Use the Copy page as Markdown button on any docs page to copy its content, then paste it into your conversation for precise context.

AI agents and automation​

If you're building an agent that needs to interact with 1Password:

  1. Use /llms.txt as the entry point for your agent to discover available documentation.
  2. Fetch individual pages as Markdown by appending .md to any URL for RAG (retrieval-augmented generation) workflows.
  3. Use the per-topic files to provide scoped context for specific tasks.

What's included​

The LLM-friendly files cover all 1Password developer documentation:

  • 1Password CLI: Command reference, guides for secrets management, shell plugins, and scripting.
  • 1Password SDKs: Python, JavaScript, and Go SDK guides for programmatic secrets access.
  • SSH & Git: SSH key management, Git commit signing, and SSH agent configuration.
  • Secrets Automation: Service accounts, Connect server, CI/CD integrations (GitHub Actions, CircleCI, Jenkins), and Kubernetes operator.
  • Environments: 1Password Environments for managing environment variables.
  • Events API: Events reporting API reference and integration guides.
  • Partnership API: API for provisioning and managing 1Password accounts programmatically.

About the llms.txt standard​

The llms.txt standard is an open specification for making website content accessible to LLMs. It provides a structured, machine-readable Markdown index at a well-known URL (/llms.txt), making it easy for AI systems to discover and consume documentation without parsing complex HTML.

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