- 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
```typescript
// 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
```json
{
"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 |
---
*Part of SkillGalaxy - 10,000+ comprehensive skills for AI-assisted development.*
GitHubで見る