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name: airbnb-listing-mcp-connector description: "MCP connector for Airbnb listing management – enables AI-powered listing optimization, guest communication, and booking management through Claude" license: Proprietary/API tags: ["business","hospitality","mcp","airbnb","travel"] difficulty: intermediate time_to_master: "4-8 weeks" version: "1.0.0"

Airbnb Listing MCP Connector

Overview

This skill enables Claude to interact with Airbnb Listing through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Airbnb Listing's REST API, allowing natural language control of Airbnb Listing operations, intelligent automation, and AI-powered assistance for Airbnb Listing workflows.

When to Use This Skill

• Listing description optimization with SEO
• Guest message drafting and auto-responses
• Pricing strategy and calendar management
• Review response generation
• Property amenity and photo management

Architecture

┌─────────────┐     ┌─────────────────┐     ┌──────────────────┐
│   Claude     │────▶│   MCP Server    │────▶│   Airbnb Listing   │
│   (Client)   │◀────│   (TypeScript)  │◀────│   (REST API      )│
└─────────────┘     └─────────────────┘     └──────────────────┘

Core Concepts

MCP Server Setup

The connector implements an MCP server that exposes Airbnb Listing operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.

Key Endpoints/Interfaces

listings management, calendar, reservations, messages, reviews

Implementation

// Airbnb Listing MCP Server Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

const server = new McpServer({
  name: "airbnb-listing-mcp-connector",
  version: "1.0.0",
});

// Tool: List/Query Resources
server.tool(
  "list_resources",
  "List and query Airbnb Listing resources with optional filters",
  {
    query: z.string().optional().describe("Search query or filter"),
    limit: z.number().optional().describe("Max results to return"),
  },
  async ({ query, limit }) => {
    // Call Airbnb Listing REST API
    const response = await fetch(`${BASE_URL}listings management`, {
      headers: { "Authorization": `Bearer ${API_KEY}` },
    });
    const data = await response.json();
    return {
      content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
    };
  }
);

// Tool: Create Resource
server.tool(
  "create_resource",
  "Create a new resource in Airbnb Listing",
  {
    name: z.string().describe("Resource name"),
    config: z.object({}).passthrough().optional().describe("Resource configuration"),
  },
  async ({ name, config }) => {
    const response = await fetch(`${BASE_URL}listings management`, {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${API_KEY}`,
        "Content-Type": "application/json",
      },
      body: JSON.stringify({ name, ...config }),
    });
    const data = await response.json();
    return {
      content: [{ type: "text", text: `Created: ${JSON.stringify(data)}` }],
    };
  }
);

// Tool: Analyze/Report
server.tool(
  "analyze",
  "AI-powered analysis of Airbnb Listing data",
  {
    type: z.string().describe("Analysis type"),
    timeframe: z.string().optional().describe("Time range for analysis"),
  },
  async ({ type, timeframe }) => {
    // Fetch data and provide AI analysis
    const response = await fetch(`${BASE_URL}listings management`, {
      headers: { "Authorization": `Bearer ${API_KEY}` },
    });
    const data = await response.json();
    return {
      content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
    };
  }
);

// Start server
const transport = new StdioServerTransport();
await server.connect(transport);

Claude Desktop Configuration

{
  "mcpServers": {
    "airbnb-listing-mcp-connector": {
      "command": "node",
      "args": ["path/to/airbnb-listing-mcp-connector/index.js"],
      "env": {
        "AIRBNB_LISTING_API_KEY": "your-api-key",
        "AIRBNB_LISTING_BASE_URL": "https://your-instance-url"
      }
    }
  }
}

Best Practices

1. Authentication: Store API keys securely using environment variables; never hardcode credentials
2. Rate Limiting: Implement request throttling to respect Airbnb Listing API rate limits
3. Error Handling: Provide clear, actionable error messages for common failure scenarios
4. Pagination: Handle paginated responses for large datasets efficiently
5. Caching: Cache frequently accessed read-only data to reduce API calls
6. Security: Validate all inputs before passing to the Airbnb Listing API; sanitize outputs
7. Logging: Log all API interactions for debugging and audit purposes

Example Prompts

"Optimize this property listing with compelling descriptions, suggest competitive pricing, and draft welcome messages"

Security Considerations

• All API credentials must be stored as environment variables
• Implement input validation and sanitization for all tool parameters
• Use HTTPS for all API communications
• Follow the principle of least privilege for API token permissions
• Audit log all write operations for compliance tracking

Resources

• Airbnb Listing Official Documentation
• MCP SDK Documentation: https://modelcontextprotocol.io
• MCP Server Examples: https://github.com/modelcontextprotocol/servers
• SkillGalaxy Repository: https://github.com/Sandeeprdy1729/skill_galaxy

Changelog

Version	Date	Changes
1.0.0	2026-04-01	Initial MCP connector skill

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