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cartoonitunes/setup-mcp-server

Name: setup-mcp-server
Author: cartoonitunes

skills/setup-mcp-server/SKILL.md

npx skillsauth add cartoonitunes/inlay-skills setup-mcp-server

Clean

TrivyContainer and dependency vulnerability scanner

Clean

SemgrepStatic code analysis for vulnerabilities

Clean

mcp-scan (Snyk)Model Context Protocol security validation

Skipped

Snyk (dep)Open source security scanning

Skipped

Socket.devSupply chain security analysis

Skipped

VirusTotalMulti-engine malware detection

Skipped

CrowdStrikeAdvanced threat intelligence

Skipped

OSV-ScannerOpen Source Vulnerability database check

Skipped

OWASP Dep-Check

Setup MCP Server Skill

Set up an MCP (Model Context Protocol) server for your website using Inlay. This lets AI agents like Claude, ChatGPT, and others interact with your site programmatically — searching pages, retrieving content, and using your site's functionality.

What is MCP?

MCP (Model Context Protocol) is a standard that lets AI agents connect to external tools and data sources. An MCP server for your website gives AI agents tools like:

get_site_info — Get site metadata and description
search_pages — Search your site's content
get_page_content — Retrieve specific page content
list_pages — Browse available pages

Workflow

Step 1: Sign Up for Inlay

Go to inlay.dev
Create an account
Add your website (enter your domain)

Step 2: Install the Embed Script

Add the Inlay embed script to your site. This enables Inlay to index your content and serve it via MCP.

Next.js (App Router):

// app/layout.tsx
import Script from 'next/script'

export default function RootLayout({ children }) {
  return (
    <html>
      <body>
        {children}
        <Script
          src="https://cdn.inlay.dev/embed.js"
          data-site-id="YOUR_SITE_ID"
          strategy="afterInteractive"
        />
      </body>
    </html>
  )
}

Next.js (Pages Router):

// pages/_app.tsx
import Script from 'next/script'

export default function App({ Component, pageProps }) {
  return (
    <>
      <Component {...pageProps} />
      <Script
        src="https://cdn.inlay.dev/embed.js"
        data-site-id="YOUR_SITE_ID"
        strategy="afterInteractive"
      />
    </>
  )
}

Astro:

<!-- src/layouts/Base.astro -->
<script src="https://cdn.inlay.dev/embed.js" data-site-id="YOUR_SITE_ID"></script>

Plain HTML:

<script src="https://cdn.inlay.dev/embed.js" data-site-id="YOUR_SITE_ID"></script>

Replace YOUR_SITE_ID with the Site ID from your Inlay dashboard.

Step 3: Verify MCP Endpoint

Once the embed script is installed and Inlay has indexed your site, your MCP endpoint is available at:

https://mcp.inlay.dev/YOUR_SITE_SLUG

Test it:

# Check MCP endpoint is responding
curl -s https://mcp.inlay.dev/YOUR_SITE_SLUG

# List available tools
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/list"}'

Step 4: Test MCP Tools

Test each tool to make sure it works:

# Get site info
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/call","params":{"name":"get_site_info","arguments":{}}}'

# Search pages
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/call","params":{"name":"search_pages","arguments":{"query":"getting started"}}}'

# Get specific page content
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/call","params":{"name":"get_page_content","arguments":{"path":"/"}}}'

Step 5: Advertise Your MCP Server

Make your MCP server discoverable:

Add to llms.txt:

## MCP
- Endpoint: https://mcp.inlay.dev/YOUR_SITE_SLUG
- Tools: get_site_info, search_pages, get_page_content, list_pages

Add meta tag (optional):

<meta name="mcp-server" content="https://mcp.inlay.dev/YOUR_SITE_SLUG">

Step 6: Verify with Audit

Run an AI readiness audit to confirm MCP is detected:

curl -s -X POST https://www.inlay.dev/api/audit \
  -H 'Content-Type: application/json' \
  -d '{"url":"https://YOUR_SITE"}'

The MCP Server category score should now be high.

Tips

Inlay re-indexes your site periodically — new pages appear automatically
The MCP server works with any AI agent that supports MCP (Claude Desktop, Cursor, etc.)
You can configure which pages are indexed in the Inlay dashboard
For private/authenticated content, check Inlay's access control settings

cartoonitunes/setup-mcp-server

skills/setup-mcp-server/SKILL.md

Set up an MCP (Model Context Protocol) server for any website via Inlay. Enables AI agents to search, browse, and interact with your site programmatically. Use when adding MCP support, enabling AI agent access, or setting up Inlay.

1 stars

tools

Updated May 8, 2026

$ install --global

skillsauth

npx skillsauth add cartoonitunes/inlay-skills setup-mcp-server

Install this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.

Security Scan Results

3 of 9 scanners reported clean

Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.

Scanners Passed

Scanners in report

Clean

TrivyContainer and dependency vulnerability scanner

95%

Clean

SemgrepStatic code analysis for vulnerabilities

95%

Clean

mcp-scan (Snyk)Model Context Protocol security validation

95%

Skipped

Snyk (dep)Open source security scanning

50%

Skipped

Socket.devSupply chain security analysis

50%

Skipped

VirusTotalMulti-engine malware detection

50%

Skipped

CrowdStrikeAdvanced threat intelligence

50%

Skipped

OSV-ScannerOpen Source Vulnerability database check

50%

Skipped

OWASP Dep-Check

50%

Last scanned: May 8, 2026, 3:34 AM131.8s1 file scanned

SKILL.md

name:: setup-mcp-server
description:: |

Setup MCP Server Skill

What is MCP?

MCP (Model Context Protocol) is a standard that lets AI agents connect to external tools and data sources. An MCP server for your website gives AI agents tools like:

get_site_info — Get site metadata and description
search_pages — Search your site's content
get_page_content — Retrieve specific page content
list_pages — Browse available pages

Workflow

Step 1: Sign Up for Inlay

Go to inlay.dev
Create an account
Add your website (enter your domain)

Step 2: Install the Embed Script

Add the Inlay embed script to your site. This enables Inlay to index your content and serve it via MCP.

Next.js (App Router):

// app/layout.tsx
import Script from 'next/script'

export default function RootLayout({ children }) {
  return (
    <html>
      <body>
        {children}
        <Script
          src="https://cdn.inlay.dev/embed.js"
          data-site-id="YOUR_SITE_ID"
          strategy="afterInteractive"
        />
      </body>
    </html>
  )
}

Next.js (Pages Router):

// pages/_app.tsx
import Script from 'next/script'

export default function App({ Component, pageProps }) {
  return (
    <>
      <Component {...pageProps} />
      <Script
        src="https://cdn.inlay.dev/embed.js"
        data-site-id="YOUR_SITE_ID"
        strategy="afterInteractive"
      />
    </>
  )
}

Astro:

<!-- src/layouts/Base.astro -->
<script src="https://cdn.inlay.dev/embed.js" data-site-id="YOUR_SITE_ID"></script>

Plain HTML:

<script src="https://cdn.inlay.dev/embed.js" data-site-id="YOUR_SITE_ID"></script>

Replace YOUR_SITE_ID with the Site ID from your Inlay dashboard.

Step 3: Verify MCP Endpoint

Once the embed script is installed and Inlay has indexed your site, your MCP endpoint is available at:

https://mcp.inlay.dev/YOUR_SITE_SLUG

Test it:

# Check MCP endpoint is responding
curl -s https://mcp.inlay.dev/YOUR_SITE_SLUG

# List available tools
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/list"}'

Step 4: Test MCP Tools

Test each tool to make sure it works:

# Get site info
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/call","params":{"name":"get_site_info","arguments":{}}}'

# Search pages
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/call","params":{"name":"search_pages","arguments":{"query":"getting started"}}}'

# Get specific page content
curl -s -X POST https://mcp.inlay.dev/YOUR_SITE_SLUG \
  -H 'Content-Type: application/json' \
  -d '{"method":"tools/call","params":{"name":"get_page_content","arguments":{"path":"/"}}}'

Step 5: Advertise Your MCP Server

Make your MCP server discoverable:

Add to llms.txt:

## MCP
- Endpoint: https://mcp.inlay.dev/YOUR_SITE_SLUG
- Tools: get_site_info, search_pages, get_page_content, list_pages

Add meta tag (optional):

<meta name="mcp-server" content="https://mcp.inlay.dev/YOUR_SITE_SLUG">

Step 6: Verify with Audit

Run an AI readiness audit to confirm MCP is detected:

curl -s -X POST https://www.inlay.dev/api/audit \
  -H 'Content-Type: application/json' \
  -d '{"url":"https://YOUR_SITE"}'

The MCP Server category score should now be high.

Tips

Inlay re-indexes your site periodically — new pages appear automatically
The MCP server works with any AI agent that supports MCP (Claude Desktop, Cursor, etc.)
You can configure which pages are indexed in the Inlay dashboard
For private/authenticated content, check Inlay's access control settings

Related Skills

cartoonitunes/setup-llms-txt

development

VerifiedTrustedCommunity

Create and configure llms.txt for any website or project. Analyzes project structure, generates llms.txt and llms-full.txt, places files in the correct location for your framework. Use when setting up llms.txt, improving AI discoverability, or making a site LLM-friendly.

1SKILL.mdUpdated May 8, 2026

cartoonitunes/setup-llms-txt

cartoonitunes/ai-readiness-audit

tools

VerifiedTrustedCommunity

Audit any website for AI agent readiness. Check llms.txt, MCP servers, structured data, semantic HTML, meta quality, and more. Use when optimizing a site for AI agents, checking AI discoverability, or preparing for AI search engines.

1SKILL.mdUpdated May 8, 2026

cartoonitunes/ai-readiness-audit

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357,764SKILL.mdUpdated Apr 10, 2026

openclaw/extensions/lobster

tools

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# Lobster Lobster executes multi-step workflows with approval checkpoints. Use it when: - User wants a repeatable automation (triage, monitor, sync) - Actions need human approval before executing (send, post, delete) - Multiple tool calls should run as one deterministic operation ## When to use Lobster | User intent | Use Lobster? | | ------------------------------------------------------ | --------------------------

357,764SKILL.mdUpdated Apr 10, 2026

openclaw/extensions/lobster

Download

For Claude Desktop. Download once, then upload the file in the app — no terminal needed.

Need help? View full Cowork setup guide →

Install manually

Choose your platform

# Clone the repo
git clone https://github.com/cartoonitunes/inlay-skills.git

# Copy into Claude Code skills folder (global)
cp -r inlay-skills/skills/setup-mcp-server ~/.claude/skills/

Claude Code Skills — official skills path docs.

Repository

cartoonitunes/inlay-skills

1 stars

Compatible with

Claude Code

OpenAI Codex CLI

ChatGPT