> ## Documentation Index
> Fetch the complete documentation index at: https://docs.stora.co/llms.txt
> Use this file to discover all available pages before exploring further.

# Developer tools

> Use AI tools, MCP, and machine-readable specs to work with the Stora API more efficiently.

This documentation site includes built-in integrations that help you work with the Stora API using AI assistants, code editors, and automation tools.

## Contextual menu

Every page in these docs has a contextual menu (look for the icons in the page header) that lets you:

* **Copy as markdown** — grab the page content for use in prompts or notes
* **Open in ChatGPT, Claude, or Perplexity** — send the current page directly to an AI assistant with one click
* **Install MCP server** — connect your docs-aware AI tools to the Stora API docs

## Documentation MCP server

The Stora docs include a hosted [Model Context Protocol](https://modelcontextprotocol.io/) (MCP) server. When connected, your AI tools can search the content of these docs directly instead of relying on training data or web search. This is a documentation search tool — it doesn't connect to the Stora API or your account data.

The MCP server URL is:

```
https://docs.stora.co/mcp
```

<Tabs>
  <Tab title="Claude Code">
    ```bash theme={null}
    claude mcp add stora-docs --transport sse https://docs.stora.co/mcp
    ```
  </Tab>

  <Tab title="Cursor">
    Add the following to your `.cursor/mcp.json`:

    ```json theme={null}
    {
      "mcpServers": {
        "stora-docs": {
          "url": "https://docs.stora.co/mcp"
        }
      }
    }
    ```
  </Tab>

  <Tab title="VS Code">
    Add the following to your `.vscode/mcp.json`:

    ```json theme={null}
    {
      "servers": {
        "stora-docs": {
          "url": "https://docs.stora.co/mcp"
        }
      }
    }
    ```
  </Tab>
</Tabs>

Once connected, your AI assistant can answer questions about the Stora API using the latest documentation rather than potentially outdated training data.

## OpenAPI specification

The full OpenAPI 3.1 specification is available in JSON format at:

```
https://docs.stora.co/2025-09/openapi.json
```

Most AI coding assistants and agent frameworks can consume this spec directly. Point your agent to the URL above and provide it with an access token.

## llms.txt

These docs automatically generate and maintain [`llms.txt`](/llms.txt) and [`llms-full.txt`](/llms-full.txt) files at the documentation root. These are an [industry standard](https://llmstxt.org/) that helps AI systems efficiently index and understand documentation — similar to how a sitemap helps search engines.

## Tips for AI integration

<Note>
  These tips apply whether you're using the MCP server, feeding the OpenAPI spec to an agent, or working with an AI assistant that has access to these docs.
</Note>

* **Start with read-only scopes.** When experimenting, limit the access token to `read` scopes to prevent unintended modifications.
* **Use idempotency keys for writes.** When the agent creates or updates resources, include an `Idempotency-Key` header to avoid duplicate operations on retries.
* **Respect rate limits.** AI agents can generate bursts of requests. Implement backoff when receiving `429` responses.