An MCP server that adds RAG-powered AI chat to any website. One command from Claude Code.
---
Tell Claude Code _"add AI chat to mysite.com"_ and it will crawl your content, build a local vector store, spin up a chat server, and hand you an embed snippet. No cloud infra. No database. Just one API key.
## Demo
```
You: "Set up AI chat for mybakery.com using this FAQ and menu content"
Claude: I'll set up RAG-powered chat for mybakery.com.
[1/4] ragchat_setup
Splitting content into sections...
Generating embeddings for 12 documents...
Domain "mybakery.com" configured with 12 documents.
[2/4] ragchat_test
Query: "What are your hours?"
Reply: "We're open Monday-Saturday 7am-6pm, and Sunday 8am-2pm."
RAG Sources: mybakery.com-3 (0.91), mybakery.com-7 (0.84)
Latency: 340ms
[3/4] ragchat_serve
Chat server running at http://localhost:3456
POST /chat ready.
[4/4] ragchat_widget
Generated embed code. Paste this into your HTML:
You: Done. Live chat on my site in under 60 seconds.
```
## Quick Start
**1. Clone and build**
```bash
git clone https://github.com/gogabrielordonez/mcp-ragchat
cd mcp-ragchat
npm install && npm run build
```
**2. Configure Claude Code** (`~/.claude/mcp.json`)
```json
{
"mcpServers": {
"ragchat": {
"command": "node",
"args": ["/absolute/path/to/mcp-ragchat/dist/mcp-server.js"],
"env": {
"OPENAI_API_KEY": "sk-..."
}
}
}
}
```
**3. Use it**
Open Claude Code and say:
> "Add AI chat to mysite.com. Here's the content: [paste your markdown]"
Claude handles the rest.
## Tools
| Tool | What it does |
|------|-------------|
| `ragchat_setup` | Seed a knowledge base from markdown content. Each `##` section becomes a searchable document with vector embeddings. |
| `ragchat_test` | Send a test message to verify RAG retrieval and LLM response quality. |
| `ragchat_serve` | Start a local HTTP chat server with CORS and input sanitization. |
| `ragchat_widget` | Generate a self-contained `
