For coding agents

These docs are written for people and for the coding agents that read them on your behalf. Every page is available as plain Markdown, and an index tells an agent where to look.

Read any page as Markdown

Add .md to the address of any docs page to get its Markdown version. For example, this page is also at /docs/resources/agents.md. The same Markdown comes back when a request sends Accept: text/markdown, and every page points to its Markdown version with <link rel="alternate" type="text/markdown">.

Start from the index

/docs/llms.txt follows the llms.txt proposal. It lists every docs page by section, each with a one-line summary and a link to its Markdown version. /docs/llms-full.txt holds every docs page in one Markdown file.

Copy a page

The Copy page button on every page copies the page as Markdown. Its menu also opens the Markdown version, or opens the page in Claude or ChatGPT with its address filled in.

Set up OpenPlanr from an agent

The agent setup guide is a Markdown file written for coding agents. Set up from your agent explains what it does and what it asks you first.

Connect over MCP

Connect a Streamable HTTP MCP client to https://openplanr.dev/docs/mcp. The server is read-only and needs no API key. search(query, section?) returns up to six passages with a title, an anchored URL and text. The optional section is a URL segment such as get-started, skills, prompts or cli. fetch_page(url) returns the same Markdown as the page's twin; it accepts /docs/... paths and https://openplanr.dev/docs/... URLs, including .md links.

For Claude Code, run:

claude mcp add --transport http openplanr-docs https://openplanr.dev/docs/mcp

For Codex, run:

codex mcp add openplanr-docs --url https://openplanr.dev/docs/mcp

For Cursor, add this entry to .cursor/mcp.json in your project, merging it with any existing servers:

{
  "mcpServers": {
    "openplanr-docs": {
      "url": "https://openplanr.dev/docs/mcp"
    }
  }
}

The endpoint is rate limited. If it replies with HTTP 429, try again later or read /docs/llms.txt and the linked Markdown pages directly. It searches the published docs without calling a model.