Provides tools for searching Airbnb listings and retrieving detailed information about specific properties, including pricing, amenities, host details, and availability.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Airbnb MCP Server search for beachfront villas in Bali for 4 adults next month"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server for searching Airbnb and get listing details.
airbnb_search
Search for Airbnb listings
Required Input: location (string)
Optional Inputs:
placeId (string)
checkin (string, YYYY-MM-DD)
checkout (string, YYYY-MM-DD)
adults (number)
children (number)
infants (number)
pets (number)
minPrice (number)
maxPrice (number)
cursor (string)
ignoreRobotsText (boolean)
Returns: Array of listings with details like name, price, location, etc.
airbnb_listing_details
Get detailed information about a specific Airbnb listing
Required Input: id (string)
Optional Inputs:
checkin (string, YYYY-MM-DD)
checkout (string, YYYY-MM-DD)
adults (number)
children (number)
infants (number)
pets (number)
ignoreRobotsText (boolean)
Returns: Detailed listing information including description, host details, amenities, pricing, etc.
Related MCP server: Airbnb MCP Server
Respects Airbnb's robots.txt rules
Uses cheerio for HTML parsing
No API key required
Returns structured JSON data
Reduces context load by flattening and picking data
Before starting make sure Node.js is installed on your desktop for npx to work.
Go to: Settings > Developer > Edit Config
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"airbnb": {
"command": "npx",
"args": [
"-y",
"@openbnb/mcp-server-airbnb"
]
}
}
}To ignore robots.txt for all requests, use this version with --ignore-robots-txt args
{
"mcpServers": {
"airbnb": {
"command": "npx",
"args": [
"-y",
"@openbnb/mcp-server-airbnb",
"--ignore-robots-txt"
]
}
}
}Restart Claude Desktop and plan your next trip that include Airbnbs!
To install mcp-server-airbnb for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @openbnb-org/mcp-server-airbnb --client claudenpm install
npm run buildThis MCP server is licensed under the MIT License.
Airbnb is a trademark of Airbnb, Inc. OpenBnB is not related to Airbnb, Inc. or its subsidiaries
Get detailed information about a specific Airbnb listing. Provide direct links to the user
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The Airbnb listing ID | |
| checkin | No | Check-in date (YYYY-MM-DD) | |
| checkout | No | Check-out date (YYYY-MM-DD) | |
| adults | No | Number of adults | |
| children | No | Number of children | |
| infants | No | Number of infants | |
| pets | No | Number of pets | |
| ignoreRobotsText | No | Ignore robots.txt rules for this request |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions returning 'detailed information' and 'direct links', which hints at read-only behavior and output format, but fails to address critical aspects like rate limits, authentication needs, error handling, or data freshness. For a tool with 8 parameters and no annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, stating the core purpose in the first sentence. The second sentence adds a usage hint without redundancy. However, it could be more structured by explicitly separating purpose from guidelines, and the vague phrase 'Provide direct links to the user' slightly reduces clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, no output schema, no annotations), the description is incomplete. It lacks details on return values, error conditions, performance expectations, and how parameters like dates affect results. Without annotations or output schema, the description should compensate more to ensure the agent can use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for all 8 parameters. This meets the baseline for high schema coverage, but the description doesn't enhance understanding of parameter interactions or provide examples, limiting its added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed information about a specific Airbnb listing.' It specifies the verb ('Get') and resource ('Airbnb listing'), making the intent unambiguous. However, it doesn't explicitly differentiate from its sibling 'airbnb_search' (which likely searches for listings rather than retrieving details for a specific one), preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance: 'Provide direct links to the user' suggests a use case for sharing results, but it offers no explicit advice on when to use this tool versus alternatives like 'airbnb_search'. There's no mention of prerequisites, exclusions, or contextual best practices, leaving significant gaps in usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for Airbnb listings with various filters and pagination. Provide direct links to the user
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes | Location to search for (city, state, etc.) | |
| placeId | No | Google Maps Place ID (overrides the location parameter) | |
| checkin | No | Check-in date (YYYY-MM-DD) | |
| checkout | No | Check-out date (YYYY-MM-DD) | |
| adults | No | Number of adults | |
| children | No | Number of children | |
| infants | No | Number of infants | |
| pets | No | Number of pets | |
| minPrice | No | Minimum price for the stay | |
| maxPrice | No | Maximum price for the stay | |
| cursor | No | Base64-encoded string used for Pagination | |
| ignoreRobotsText | No | Ignore robots.txt rules for this request |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'pagination' (via the cursor parameter) and 'Provide direct links to the user,' which adds some context about output behavior. However, it lacks critical details such as rate limits, authentication requirements, error handling, or what the search results include (e.g., format, fields). For a search tool with 12 parameters, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that are front-loaded: the first states the core purpose, and the second adds output context. There's no wasted text, but it could be slightly more structured (e.g., separating purpose from behavioral notes).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format (beyond 'direct links'), error cases, authentication, or rate limits. For a search tool with many filters and pagination, more context is needed to guide effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 12 parameters. The description adds minimal value beyond the schema, mentioning 'various filters and pagination' which aligns with parameters like location, dates, prices, and cursor. It doesn't provide additional syntax, format details, or usage examples beyond what's in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search for Airbnb listings with various filters and pagination.' It specifies the verb ('search'), resource ('Airbnb listings'), and scope ('with various filters and pagination'). However, it doesn't explicitly differentiate from its sibling tool 'airbnb_listing_details' beyond the general search vs. details distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'Provide direct links to the user,' which hints at output format but doesn't clarify usage context, prerequisites, or exclusions. There's no mention of when to choose this over 'airbnb_listing_details' or other potential tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0airbnb_listing_detailsairbnb_searchThe 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.
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If you are the server author, to access and configure the admin panel.
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