You can connect ScitiX Docs to AI tools such as Claude Code, Codex, and Cursor. The AI tool can then answer GPU Cloud questions based on the documentation, such as how to choose a product, create instances, manage Kubernetes clusters, use storage, or configure monitoring and alerts.
Choose a method
We recommend using MCP first. MCP is best for querying ScitiX documentation continuously from an IDE, coding agent, or desktop AI client. The AI tool can retrieve relevant documentation on demand, without requiring you to copy page links or page content each time.
If your AI tool does not support MCP, choose another method based on your use case.
MCP access
If your AI tool supports Model Context Protocol (MCP), you can connect it to ScitiX documentation. After connection, the AI tool can search relevant documentation and answer questions based on the docs.
Access URL
Use the following MCP server URL when adding ScitiX Docs to your AI tool.
After connection, the AI tool can use the following documentation tools:
Example questions
- Should I choose CES instances or Kubernetes clusters?
- Should shared data use GPFS or OSS?
- How do I view monitoring data?
- How do I subscribe to alerts?
Claude Code is primarily a command-line workflow. In the project directory where you want to use ScitiX Docs, run:
After configuration, run the following command to check the connection:
If you use a Codex client that supports graphical MCP configuration, you can add an MCP server in the app and set the server URL to https://docs.scitix.ai/mcp.
If you want to reuse the configuration across projects or IDEs, use the CLI or configuration file.
Run the following command to add the ScitiX Docs MCP server:
After configuration, run the following command to check the connection:
You can also edit the Codex configuration file, such as ~/.codex/config.toml, and add:
Other reading methods
Use skill.md
skill.md describes the documentation site and product capabilities to AI agents. It is useful for tools that support skills or agent context.
Use llms.txt
llms.txt provides an index of the documentation pages. It is useful when you want AI to understand what pages are available.
Use llms-full.txt
llms-full.txt provides more complete documentation content. It is useful when an AI tool needs a larger documentation context at once.
llms-full.txt may contain a large amount of content. Some AI tools have context length limits. If the content is too long, use MCP, llms.txt, or single-page Markdown instead.
Use single-page Markdown
Every documentation page can be read in Markdown format. Add .md to the page URL to get a plain-text version that is easier for AI tools to read.
For example:
Usage recommendations
- For GPU Cloud concepts, setup steps, and configuration details, prefer MCP or a specific Markdown page.
- For resource inventory, instance status, cluster status, orders, and console configuration, also check the console.
- If an AI answer conflicts with the documentation page, rely on the documentation page.
