Airbnb MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| airbnb_searchC | Search for Airbnb listings with various filters and pagination. Provide direct links to the user |
| airbnb_listing_detailsC | Get detailed information about a specific Airbnb listing. Provide direct links to the user |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one retrieves detailed information for a specific listing, while the other searches for listings with filters and pagination. There is no overlap or ambiguity between these functions, making it easy for an agent to choose the right tool based on the task.
Both tool names follow a consistent pattern: 'airbnb_' prefix followed by a descriptive verb_noun combination (listing_details and search). This uniformity enhances readability and predictability, making the tool set easy to understand and use.
With only two tools, the server feels under-scoped for an Airbnb domain, which typically involves more operations like booking, user management, reviews, or listing creation. While the tools cover basic retrieval and search, the count is too low to support comprehensive agent workflows, limiting functionality.
The tool set is severely incomplete for an Airbnb server, lacking essential operations such as booking a listing, managing user accounts, handling reviews, or creating/updating listings. This creates significant gaps that will likely cause agent failures when attempting full interactions with the platform.