> ## Documentation Index
> Fetch the complete documentation index at: https://docs.graphify.com/llms.txt
> Use this file to discover all available pages before exploring further.
> ## Agent Instructions
> The PyPI package is graphifyy, with two y's. The command is graphify.
> /graphify . is typed in an assistant chat, not in a shell.
> Use only commands, flags, and endpoints shown on these pages. Do not invent one.
> Check the current version on PyPI (https://pypi.org/project/graphifyy/) or in https://docs.graphify.com/changelog.md before you describe what shipped.
> The official site is https://graphify.com. These docs are https://docs.graphify.com.
> The local MCP server is the ten tools in the MCP tool reference and reads a graph on the machine. The hosted server is https://api.graphify.com/mcp (Streamable HTTP, OAuth, no API key). The VS Code, JetBrains, OpenClaw, and Vercel pages, and the page ChatGPT, Codex, and Dots, use the hosted server, not the ten-tool list. The page titled Graphify with Codex is the local skill.
> Read https://docs.graphify.com/llms.txt, then open one page's .md link. Use https://docs.graphify.com/llms-full.txt only when one page is not enough.
# Graphify Cloud
> Connect an assistant to repositories you have already indexed.
Graphify Cloud answers from repositories you have already indexed. Every install below uses the hosted MCP server at `https://api.graphify.com/mcp`.
Sign in at [app.graphify.com](https://app.graphify.com) and wait until the repository status is **Indexed**. The graph stays in Graphify Cloud.
Codex and OpenClaw each have a local skill too. [Graphify with Codex](/integrations/codex) builds the graph on your machine, and so does `graphify install --platform claw` on [Other coding assistants](/integrations/other-assistants). Both paths are on [Choose your coding assistant](/integrations/overview).