Build with AI

Rampnow’s docs are published in formats AI tools can read directly. Connect your coding agent to them, and it works from the current API instead of guessing from its training data or from pages you paste in.

MCP server

Your agent searches and reads the docs while it works

llms.txt

An index of every page, or the whole site in one file

Markdown export

Any page as clean Markdown

Agent skill

A short brief that tells agents how to integrate Rampnow

MCP server

The docs run a hosted Model Context Protocol server at:

https://docs.rampnow.io/mcp

It gives your agent two read-only tools: one searches the docs, the other reads full pages and the OpenAPI spec. It needs no authentication.

Claude Code
Claude
Cursor
VS Code
ChatGPT

claude mcp add --transport http rampnow-docs https://docs.rampnow.io/mcp

In Claude, open Settings → Connectors, choose Add custom connector, name it Rampnow Docs and enter https://docs.rampnow.io/mcp as the URL.

Add the server to ~/.cursor/mcp.json (all projects) or .cursor/mcp.json (one project):

{
  "mcpServers": {
    "rampnow-docs": {
      "url": "https://docs.rampnow.io/mcp"
    }
  }
}

Add the server to .vscode/mcp.json:

{
  "servers": {
    "rampnow-docs": {
      "type": "http",
      "url": "https://docs.rampnow.io/mcp"
    }
  }
}

In ChatGPT, open Settings → Apps & Connectors, create a connector and enter https://docs.rampnow.io/mcp as the server URL. Custom connectors need developer mode turned on.

Clients that support discovery can find the server at https://docs.rampnow.io/.well-known/mcp. You can also add the server from any docs page: open the page menu at the top of the page and choose Connect to Cursor, Connect to VS Code or Copy MCP server URL.

The MCP server searches the documentation only. It doesn’t call the Rampnow API, see your orders or use your API keys.

llms.txt

Two files follow the llms.txt convention:

File	Contents	Use it when
`/llms.txt`	Every page, with its title, description and Markdown link	Your agent fetches the pages it needs
`/llms-full.txt`	The full text of every page in one file	You give a model the whole site in one go

To ask questions about the full docs from your own code, send llms-full.txt as a cached system prompt. Follow-up questions then reuse the cache, which costs less and responds faster:

Python

import urllib.request

import anthropic

with urllib.request.urlopen("https://docs.rampnow.io/llms-full.txt") as res:
    docs = res.read().decode("utf-8")

client = anthropic.Anthropic()

response = client.beta.messages.create(
    model="claude-opus-5-5",
    max_tokens=16000,
    betas=["server-side-fallback-2026-07-01"],
    fallbacks="default",
    system=[
        {"type": "text", "text": "Answer using the Rampnow documentation below."},
        {"type": "text", "text": docs, "cache_control": {"type": "ephemeral"}},
    ],
    messages=[
        {"role": "user", "content": "How do I sign a request to the quote endpoint?"}
    ],
)

if response.stop_reason == "refusal":
    print("The request was declined.")
else:
    print("".join(block.text for block in response.content if block.type == "text"))

Markdown export

Every page is also available as Markdown. Add .md to its URL:

A request for the normal page URL with an Accept: text/markdown header returns the same Markdown:

curl -H "Accept: text/markdown" https://docs.rampnow.io/api-reference/authentication

To get a page without leaving the site, open the page menu at the top of any page. From there you can copy the page as Markdown or open it in ChatGPT, Claude or Perplexity.

Agent skill

/skill.md is a short brief for coding agents, in the Agent Skills format. It covers which product to use, authentication, the order flow, statuses and common mistakes. It links to the full pages for everything else. Install it into your agent with:

npx skills add https://docs.rampnow.io

Recommended setup

Connect the MCP server

Add the MCP server to your editor or agent so it can look things up as it works.

Tell your agent which product you're building

Rampnow has two integrations that don’t mix. Start your agent on the right quickstart:

Widget or SDK (no backend, public key only): Widget or SDK
Intent API (your backend creates signed orders): Intent API

Give it the full docs for one-off tasks

For a single large task, such as writing a whole integration, put llms-full.txt in context with prompt caching.

Check what it builds

Check generated requests against the API reference. Test the signing code against the test vector. Run the sandbox test plan before going live.

Never paste your API secret into a prompt or an agent’s context. Keep it in your server’s environment, and have your agent write code that reads it from there.

Learn about Rampnow

What's Supported

Integrations

Help

Build with AI

MCP server

llms.txt

Markdown export

Agent skill

MCP server

llms.txt

Markdown export

Agent skill

Recommended setup

MCP server

llms.txt

Markdown export

Agent skill

​MCP server

​llms.txt

​Markdown export

​Agent skill

​Recommended setup

MCP server

llms.txt

Markdown export

Agent skill

Recommended setup