# Docs for AI agents (/tools/ai-llms)

Shelby documentation provides two methods for programmatic access optimized for AI agents and LLMs.

## Full Documentation Endpoint

Get all documentation in a single plain text file.

```bash
curl https://docs.shelby.xyz/llms-full.txt
```

The response includes all pages formatted as:

```text
# Page Title (URL)

Page content in markdown...

# Next Page Title (URL)

Next page content...
```

## Individual Page Markdown

### Direct URL

Access any page's markdown content by appending `.mdx` or `.md` to the page URL:

```bash
curl https://docs.shelby.xyz/tools/s3-gateway.mdx
# or
curl https://docs.shelby.xyz/tools/s3-gateway.md
```

Examples:

* `/tools/s3-gateway` → `/tools/s3-gateway.mdx` or `/tools/s3-gateway.md`
* `/protocol/quickstart` → `/protocol/quickstart.mdx` or `/protocol/quickstart.md`
* `/tools/mcp` → `/tools/mcp.mdx` or `/tools/mcp.md`

### Accept Header

Alternatively, request any documentation page as markdown by setting the `Accept` header to `text/markdown`:

```bash
curl -H "Accept: text/markdown" https://docs.shelby.xyz/protocol/quickstart
```

This works for all documentation sections:

* `/protocol/*` - Getting started and how Shelby works
* `/tools/*` - The S3 API and MCP server

## Runnable examples and agent skills

Two repositories are written for agents to read alongside these docs:

* **[shelby-quickstart](https://github.com/shelby/shelby-quickstart)** has a runnable,
  self-checking example for each client these docs cover. Its `AGENTS.md` lists where
  code written for Amazon S3 breaks on Shelby, and `make doctor` checks credentials
  before any code runs.
* **[shelby-skills](https://github.com/shelby/shelby-skills)** packages the same guidance
  as an agent skill, so the agent has it while working in your project.