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Posted on Oct 29

Build and Train a Website Chatbot From Claude Code or Cursor (MCP Walkthrough)

#mcp #ai #chatbot #cursor

You can create a support chatbot, train it on your sitemap, and test its answers without leaving your editor. The loop is five tool calls: create_chatbot, add_chatbot_content, chatbot_status, ask_chatbot, and list_chatbots when you come back later. This walkthrough uses Appie.run's MCP server, with every tool name, argument and credit cost taken from appie.run/docs/mcp on 28 Oct 2026.

Disclosure: Appie.run publishes this post, and the server used here is ours.

This is the third walkthrough in the series, after Reddit threads and reply drafts and LinkedIn profiles and leads. If you've done either, skip to Step 3.

What you need

An Appie project. The Free plan has 500 credits and needs no credit card.
A project API key that starts with esk_.
Cursor, Claude Code, or another MCP client that supports remote servers with custom headers.
A public sitemap, or a few pages of text you want the bot to answer from.

Step 1: Create the key

In Appie, open the project and go to API in the sidebar. A project admin generates one esk_ key. Two things worth knowing:

The same key is used by Event Store. Regenerating it stops both immediately.
The key has no balance of its own. Paid calls run on the project's credits, then the project owner's. Every tool result includes credits_remaining.

export APPIE_API_KEY=esk_YOUR_KEY

Keep it out of git.

Step 2: Add the server

Cursor. From Appie's docs:

{
  "mcpServers": {
    "appie": {
      "url": "https://appie.run/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Claude Code.

claude mcp add --transport http appie https://appie.run/mcp \
  --header "Authorization: Bearer $APPIE_API_KEY"

Run claude mcp list to check the connection. A request with a placeholder key returned HTTP 401 when we tried it on 28 Oct 2026, which is the expected response for a bad key.

Step 3: Find the sitemap you'll train on

The bot learns fastest from a sitemap, because one call pulls in every page it lists. If you don't know where your sitemap lives, Appie's free Sitemap Finder and Checker reads your robots.txt Sitemap: lines and the usual paths (including the WordPress path) and reports which files load and how many URLs they list.

A tip before you train: a sitemap often includes pages you don't want a support bot quoting, such as old blog posts, legal archives or job ads. If yours is noisy, train on a smaller sitemap file or on specific URLs instead.

Step 4: Create the bot

Ask your agent: "Create an Appie chatbot called Support Bot for example.com with a short system prompt."

The agent calls create_chatbot. name is required. Optional fields are system_prompt, openai_model (gpt-4o-mini, gpt-4o or gpt-3.5-turbo) and temperature from 0 to 1. Creation is free. Illustrative arguments:

{
  "name": "Support Bot",
  "system_prompt": "Answer questions about Example Co using only the provided content. If the answer is not in the content, say you don't know and suggest emailing support.",
  "openai_model": "gpt-4o-mini",
  "temperature": 0.2
}

A low temperature keeps answers close to your content. Note the returned chatbot_id; every later call needs it.

Step 5: Add knowledge

Call add_chatbot_content with one of these content_type values:

sitemap: Fields: url (http or https); Use it for: A whole site or section
url: Fields: url (http or https); Use it for: One page, such as pricing or a returns policy
text: Fields: title, content; Use it for: Facts that aren't on the site yet
article: Fields: article_id; Use it for: An article from Appie's Content Writer in the same project

Illustrative calls:

{ "chatbot_id": "YOUR_BOT_ID", "content_type": "sitemap", "url": "https://www.example.com/sitemap.xml" }

{
  "chatbot_id": "YOUR_BOT_ID",
  "content_type": "text",
  "title": "Support hours",
  "content": "Support replies Monday to Friday, 9am to 6pm CET. Email support@example.com."
}

The text type is handy for the questions your site never answers clearly: support hours, refund windows, which plan includes what.

Step 6: Wait for training

Processing runs in the background. Call chatbot_status with the chatbot_id to read the bot's training status and its recent sources. It's free, so poll it as often as you like. A prompt that works well:

"Check chatbot_status for YOUR_BOT_ID every 30 seconds until training finishes, then list the sources it added."

Step 7: Test it before customers do

ask_chatbot sends a message to a chatbot_id and returns a reply. It costs 1 credit per call. Pass the session_id from a previous reply to continue the same conversation, which lets you test follow-up questions.

Write a short test set and have your agent run it:

Three questions the site answers clearly (pricing, a feature, a policy).
Two questions it answers only in passing.
Two questions it doesn't answer at all. The bot should say it doesn't know, not guess.
One follow-up in the same session ("And for the annual plan?").

Ten questions cost 10 credits. If an answer is wrong, the fix is usually the content, not the prompt: add a text source with the correct fact, wait for chatbot_status, and ask again.

Step 8: Put it on your site

The MCP tools cover building, training and testing. To go live, open the chatbot in the Appie dashboard. Per appie.run/ai-chatbots, you embed it with a script tag (or the Shopify app embed), and the dashboard adds lead capture, CSV export and webhooks, and analytics.

Prompts to paste

"List my Appie chatbots and their training status."
"Create a chatbot for example.com, train it on https://www.example.com/sitemap.xml, and tell me when training is done."
"Add a text source titled Refund policy with this content: ..."
"Ask the bot these eight questions, one by one, and give me a table of question, reply, and whether the reply is supported by our site."
"Show credits_remaining after each paid call."

What it costs

list_chatbots: Credits (as of 28 Oct 2026): 0
create_chatbot: Credits (as of 28 Oct 2026): 0
add_chatbot_content: Credits (as of 28 Oct 2026): No cost stated in the docs
chatbot_status: Credits (as of 28 Oct 2026): 0
ask_chatbot: Credits (as of 28 Oct 2026): 1 per message

Building a bot is free on the pricing page too; conversations use chatbot query credits. Paid plans are Starter at $19 a month (2,000 credits) and Standard at $49 a month (5,000 credits), per appie.run/pricing.

Troubleshooting

HTTP 401. The key is missing, wrong, or was regenerated.
app_not_allowed. The person who generated the key can't use the chatbots app in that project. A project owner can use every app.
insufficient_credits. The response includes required and available.
not_found. The bot or article ID belongs to another project.
Answers ignore a page. Check chatbot_status to confirm the source was added, then ask about that page directly.

Errors come back as an MCP tool error whose text is JSON with error and message, so your agent can read and explain them.

The same actions are also available as an HTTP API and CLI; see appie.run/docs/mcp. The repo is on GitHub.

RG, Founder, Appie.run

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