Cloudflare MCP Server for Static Sites

Turn your static website into an AI-accessible knowledge base. This project deploys a Cloudflare Worker that implements the Model Context Protocol (MCP). AI tools like Claude can then search and retrieve your content directly.

Cloudflare is well-suited for hosting remote MCP servers — its Workers platform handles the transport layer, and Durable Objects maintain persistent client sessions.

Why This Matters

AI assistants answer questions based on their training data, which may be outdated or incomplete. They can't search your website unless you give them a way to do so. This MCP server can be an AI-native bridge that allows these tools to get up-to-date information when they need it.

You might use this to:

• Help users find answers in your documentation
• Give AI assistants access to your blog's content
• Let AI tools cite your articles with accurate, up-to-date information

How It Works

┌─────────────────────────────────────────────────────────────────────────┐
│                           Your Static Site                              │
│                    (Markdown files with frontmatter)                    │
└──────────────────────────────┬──────────────────────────────────────────┘
                               │
                               ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                             Adapter                                     │
│         (Astro, Hugo, or Generic — runs at build time)                  │
│                                                                         │
│   Scans your content files, extracts metadata from frontmatter,         │
│   and generates a search-index.json file.                               │
└──────────────────────────────┬──────────────────────────────────────────┘
                               │
                               ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                         Cloudflare R2                                   │
│                                                                         │
│   Stores the search index. Only your Worker can access it.              │
│   The Worker caches the index in memory for one hour.                   │
└──────────────────────────────┬──────────────────────────────────────────┘
                               │
                               ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                       Cloudflare Worker                                 │
│                                                                         │
│   Implements the MCP server. Uses Fuse.js for fuzzy search.             │
│   Durable Objects maintain persistent sessions with MCP clients.        │
└──────────────────────────────┬──────────────────────────────────────────┘
                               │
                               ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                          MCP Clients                                    │
│           (Claude Desktop, Claude Code, Cursor, etc.)                   │
│                                                                         │
│   Tools available to the AI:                                            │
│   • search_<prefix> — Find content by keywords                          │
│   • get_article     — Retrieve a specific page by URL                   │
│   • get_index_info  — Get index statistics                              │
└─────────────────────────────────────────────────────────────────────────┘

Prerequisites

Quick Start

You can follow these steps manually or point an AI coding tool (Claude Code, Cursor, etc.) at this repo and ask it to set things up. Either way, you'll need a Cloudflare account and these details about your site:

• Site name and domain (e.g., "My Blog" and "blog.example.com")
• Content directory path to your markdown files
• Tool prefix for MCP tool names (e.g., "myblog" → search_myblog)
• MCP endpoint domain (e.g., "mcp.example.com")

1. Clone and Install

git clone https://github.com/lennyzeltser/cloudflare-mcp-for-static-sites.git my-site-mcp
cd my-site-mcp
bun install

2. Configure

Edit wrangler.jsonc:

{
  "name": "my-site-mcp-server",
  "routes": [
    { "pattern": "mcp.example.com", "custom_domain": true }
  ],
  "r2_buckets": [
    { "binding": "SEARCH_BUCKET", "bucket_name": "my-site-mcp-data" }
  ]
}

3. Create R2 Bucket

npx wrangler r2 bucket create my-site-mcp-data

4. Generate and Upload Index

Pick an adapter for your site (see Adapters):

node adapters/generic/generate-index.js \
  --content-dir=../my-site/content \
  --site-name="My Site" \
  --site-domain="example.com" \
  --tool-prefix="mysite"

npx wrangler r2 object put my-site-mcp-data/search-index.json \
  --file=./search-index.json \
  --content-type=application/json

5. Deploy

bun run deploy

Your MCP server is now running. Connect an MCP client to start searching.

CI/CD: The included GitHub Actions workflow (.github/workflows/deploy.yml) is set to manual trigger only. To deploy via GitHub Actions, go to Actions → Deploy → Run workflow. To enable auto-deploy on push, edit the workflow and add push: branches: [main] to the triggers.

MCP Client Setup

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "my-site": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.example.com/sse"]
    }
  }
}

Claude Code

claude mcp add my-site --transport sse https://mcp.example.com/sse

Cursor

Add to your Cursor mcp.json:

{
  "mcpServers": {
    "my-site": {
      "url": "https://mcp.example.com/sse"
    }
  }
}

Other Clients

Use the mcp-remote package to connect via the /sse endpoint (SSE transport) or /mcp endpoint (streamable HTTP).

Available Tools

Adapters

An adapter generates the search index from your content. It scans your files, extracts frontmatter metadata, and outputs search-index.json.

Each adapter handles the specifics of a particular static site generator.

Generic (Markdown)

Works with any site that uses markdown files with YAML frontmatter.

node adapters/generic/generate-index.js \
  --content-dir=./content \
  --site-name="My Website" \
  --site-domain="example.com" \
  --tool-prefix="mysite" \
  --output=./search-index.json

See adapters/generic/README.md.

Astro

An Astro integration that generates the index at build time.

// astro.config.mjs
import { searchIndexIntegration } from './src/integrations/search-index.mjs';

export default defineConfig({
  integrations: [
    searchIndexIntegration({
      siteName: 'My Blog',
      siteDomain: 'blog.example.com',
      toolPrefix: 'myblog',
    }),
  ],
});

See adapters/astro/README.md.

Hugo

A Node.js script that handles both TOML and YAML frontmatter.

node adapters/hugo/generate-index.js \
  --content-dir=./content \
  --site-name="My Hugo Site" \
  --site-domain="example.com"

See adapters/hugo/README.md.

Writing Your Own Adapter

If your static site generator isn't listed, you can write an adapter. It just needs to output JSON in the v3.0 format.

Your adapter should:

1. Find your content files (markdown, MDX, HTML, etc.)
2. Extract metadata from frontmatter (title, date, tags)
3. Extract body text for search
4. Map file paths to URLs
5. Write search-index.json

Here's a template:

import { writeFileSync } from 'fs';

const pages = [/* your content processing logic */];

const index = {
  version: "3.0",
  generated: new Date().toISOString(),
  site: {
    name: "My Site",
    domain: "example.com",
    description: "Brief description for the MCP tool",
    toolPrefix: "mysite",
  },
  pageCount: pages.length,
  pages: pages.map(page => ({
    url: page.url,           // Required: starts with /
    title: page.title,       // Required
    abstract: page.summary,  // Optional
    date: page.date,         // Optional: YYYY-MM-DD
    topics: page.tags,       // Optional: array
    body: page.content,      // Recommended for search quality
  })),
};

writeFileSync("search-index.json", JSON.stringify(index, null, 2));

Validate your index:

bun scripts/validate-index.ts ./search-index.json

Upload to R2:

npx wrangler r2 object put my-site-mcp-data/search-index.json \
  --file=./search-index.json \
  --content-type=application/json

Configuration

wrangler.jsonc

For testing, you can use a workers.dev subdomain instead of a custom domain:

"workers_dev": true,
// Comment out "routes"

Index Format

The search index follows the v3.0 schema:

{
  "version": "3.0",
  "generated": "2025-01-15T12:00:00.000Z",
  "site": {
    "name": "My Website",
    "domain": "example.com",
    "description": "A site about interesting topics",
    "toolPrefix": "mysite"
  },
  "pageCount": 42,
  "pages": [
    {
      "url": "/about",
      "title": "About Us",
      "abstract": "Learn about our team.",
      "date": "2025-01-01",
      "topics": ["about", "team"],
      "body": "Full page content..."
    }
  ]
}

Threat Model

This MCP server is designed for public content only. Consider these security characteristics before deploying:

What's Exposed

Assumptions

• Your content is already public. The indexed pages come from a public website. This server makes them AI-searchable, not newly public.
• R2 is not the security boundary. While the R2 bucket is private, the Worker exposes its contents through MCP tools. Anyone with the endpoint URL can query all indexed content.
• No authentication. The MCP server accepts connections from any client. There's no API key, OAuth, or access control.

Not Designed For

• Private or internal documentation
• Content requiring authentication or authorization
• Partial access control (all-or-nothing visibility)

Recommendations

If you need access control, consider:

• Cloudflare Access for authentication at the Worker level
• A separate private deployment for internal content
• Excluding sensitive pages from the search index

Development

bun run dev          # Local development server
bun run type-check   # TypeScript checking
bun run lint:fix     # Lint and fix
bun run format       # Format code
bun run deploy       # Deploy to Cloudflare

Troubleshooting

"Search index not found in R2 bucket"

1. Check the bucket exists: npx wrangler r2 bucket list
2. Check the file was uploaded: npx wrangler r2 object list my-site-mcp-data
3. Verify the bucket name in wrangler.jsonc matches

MCP client won't connect

1. Use the correct endpoint: /sse for SSE, /mcp for HTTP
2. Visit your worker URL in a browser — you should see JSON
3. Make sure the URL includes https://

Search returns no results

1. Validate your index: bun scripts/validate-index.ts ./search-index.json
2. Check that pages have body content
3. Try broader search terms

Wrong tool names

Tool names come from toolPrefix in your search index. Regenerate and re-upload the index with the correct value.

Local development

You need a local copy of the search index:

mkdir -p .wrangler/state/r2/my-site-mcp-data
cp search-index.json .wrangler/state/r2/my-site-mcp-data/search-index.json

Examples

Two sites using this approach:

REMnux Documentation

MCP server for REMnux, the Linux toolkit for malware analysis.

Repo: github.com/REMnux/remnux-docs-mcp-server

# Claude Code
claude mcp add remnux-docs --transport sse https://docs-mcp.remnux.org/sse

Lenny Zeltser's Website

MCP server for zeltser.com, covering malware analysis, incident response, and security leadership.

# Claude Code
claude mcp add zeltser-search --transport sse https://website-mcp.zeltser.com/sse

Author

Lenny Zeltser is a cybersecurity leader who builds security programs, tools, and educational content. He serves as CISO at Axonius, created the REMnux malware analysis toolkit, and authored SANS courses on reverse-engineering malware and cybersecurity writing. He holds an MBA from MIT Sloan and a Computer Science degree from the University of Pennsylvania. More at zeltser.com.