{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-openbnbmcp-server-airbnb","slug":"npm-openbnbmcp-server-airbnb","name":"@openbnb/mcp-server-airbnb","type":"mcp","url":"https://www.npmjs.com/package/@openbnb/mcp-server-airbnb","page_url":"https://unfragile.ai/npm-openbnbmcp-server-airbnb","categories":["mcp-servers"],"tags":["airbnb","vacation rental","travel"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-openbnbmcp-server-airbnb__cap_0","uri":"capability://search.retrieval.airbnb.listing.search.with.location.and.date.filtering","name":"airbnb listing search with location and date filtering","description":"Executes parameterized searches against Airbnb's listing database using location coordinates, check-in/check-out dates, guest count, and property type filters. Implements MCP tool protocol to expose search as a callable function with structured input validation, returning paginated result sets with listing metadata. Abstracts Airbnb's web scraping or API layer behind a standardized MCP interface, enabling LLM agents to compose multi-step travel planning workflows without direct HTTP handling.","intents":["Search for available vacation rentals in a specific location for given dates","Filter Airbnb listings by guest capacity and property type to narrow results","Integrate Airbnb search into an LLM agent that plans multi-city trips","Retrieve paginated listing results programmatically without browser automation"],"best_for":["LLM agents and AI assistants building travel planning workflows","Developers integrating Airbnb data into multi-provider booking systems","Travel recommendation systems that need real-time availability data"],"limitations":["Depends on Airbnb's underlying data source stability — scraping-based implementations may break with UI changes","No authentication support — searches limited to public listing data only","Pagination may be limited by Airbnb's rate limiting or result set caps","No real-time pricing updates — cached or delayed pricing data possible"],"requires":["MCP client implementation (Claude Desktop, custom MCP host, or compatible LLM framework)","Node.js 16+ runtime for the MCP server process","Network access to Airbnb's data source (web or API endpoint)"],"input_types":["structured JSON with location (latitude/longitude or place name), check-in date, check-out date, guest count, property type filter"],"output_types":["JSON array of listing objects with id, title, location, price, rating, image URLs, amenities, host info, availability status"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-openbnbmcp-server-airbnb__cap_1","uri":"capability://search.retrieval.airbnb.listing.detail.retrieval.with.full.property.metadata","name":"airbnb listing detail retrieval with full property metadata","description":"Fetches comprehensive property information for a specific Airbnb listing ID, including description, amenities, house rules, cancellation policy, host profile, reviews, and booking calendar. Implements MCP tool that accepts a listing ID and returns a structured object with all publicly available metadata. Enables agents to drill down from search results into detailed property information for decision-making or comparison workflows.","intents":["Get full property details and amenities for a specific Airbnb listing","Retrieve host information, reviews, and cancellation policies for comparison","Extract house rules and booking constraints to validate against user preferences","Build a detailed property card or recommendation summary from listing metadata"],"best_for":["Travel planning agents that need to evaluate properties in detail before recommending","Comparison tools that aggregate Airbnb listings with other rental platforms","Booking assistants that validate property constraints against user requirements"],"limitations":["Requires valid Airbnb listing ID — no fuzzy matching or search-to-detail chaining built-in","Review data may be paginated or truncated — full review history may not be available","Pricing and availability calendar may be cached or stale","Host contact information not exposed — only public profile data available"],"requires":["MCP client compatible with tool calling","Node.js 16+ runtime","Valid Airbnb listing ID (typically 8-10 digit numeric ID)"],"input_types":["string: Airbnb listing ID"],"output_types":["JSON object with nested structure: title, description, location, price, rating, amenities array, house rules array, cancellation policy, host object (name, avatar, response rate, verification status), reviews array, booking calendar"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-openbnbmcp-server-airbnb__cap_2","uri":"capability://tool.use.integration.mcp.tool.schema.registration.and.llm.agent.binding","name":"mcp tool schema registration and llm agent binding","description":"Registers Airbnb search and listing detail operations as MCP tools with JSON schema definitions, enabling Claude and other LLM agents to discover, understand, and invoke these capabilities through the MCP protocol. Implements tool schema with parameter definitions, descriptions, and required/optional field specifications. Handles tool invocation routing, parameter validation, and response serialization back to the LLM agent.","intents":["Enable Claude to discover and call Airbnb search as a native tool without custom prompting","Define parameter schemas so LLMs understand what inputs are required for each operation","Route tool calls from LLM agents to the correct backend handler with validation","Return structured responses that agents can parse and use in multi-step workflows"],"best_for":["Developers building Claude-powered travel assistants or booking agents","Teams integrating Airbnb into multi-tool LLM agent systems","MCP host implementations that need to expose travel data to language models"],"limitations":["Tool schema must be manually maintained — no automatic schema generation from backend code","Parameter validation is schema-based only — no runtime type coercion","Tool discovery requires MCP client to parse and cache schema — no dynamic schema updates without reconnection","Error handling relies on MCP error protocol — custom error codes may not be understood by all LLM clients"],"requires":["MCP server implementation (Node.js)","MCP client that supports tool calling (Claude, custom LLM framework)","JSON schema knowledge for defining tool parameters"],"input_types":["JSON schema definitions for tool parameters"],"output_types":["MCP tool call responses with structured JSON results"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-openbnbmcp-server-airbnb__cap_3","uri":"capability://planning.reasoning.multi.step.travel.planning.workflow.orchestration","name":"multi-step travel planning workflow orchestration","description":"Enables LLM agents to compose search and detail retrieval operations into multi-step workflows (e.g., search locations → filter results → retrieve details → compare properties → build recommendation). Implements MCP tool chaining where agent can call search, iterate through results, fetch details for promising listings, and aggregate data for decision-making. Agent maintains context across tool calls and uses intermediate results to refine subsequent queries.","intents":["Build a travel planning agent that searches multiple locations and compares properties","Create a booking assistant that validates listings against user constraints before recommending","Implement a price comparison workflow that searches dates and aggregates results across properties","Enable agents to refine searches based on initial results (e.g., search → filter → search nearby → compare)"],"best_for":["LLM agents that need to execute complex travel planning logic with multiple data lookups","Travel recommendation systems that require multi-step reasoning and comparison","Booking assistants that validate properties against user preferences before suggesting"],"limitations":["Workflow complexity depends on LLM's reasoning ability — agents may not optimize search strategy","No built-in state persistence — agent context lost between sessions unless externally stored","Tool call latency compounds across steps — multi-step workflows may be slow if backend is not optimized","No transaction semantics — partial failures in multi-step workflows require manual recovery logic"],"requires":["MCP client with multi-turn conversation support","LLM with sufficient context window to maintain workflow state","Backend infrastructure to handle sequential tool calls without rate limiting"],"input_types":["Natural language user request (e.g., 'Find me a 2-bedroom in Barcelona for next week under €150/night')"],"output_types":["Structured recommendation with ranked listings, comparison matrix, and booking links"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-openbnbmcp-server-airbnb__cap_4","uri":"capability://tool.use.integration.airbnb.data.source.abstraction.and.backend.integration","name":"airbnb data source abstraction and backend integration","description":"Abstracts the underlying Airbnb data source (web scraping, unofficial API, or other integration) behind the MCP server interface, isolating clients from implementation details. Handles data fetching, transformation, and caching at the server layer. Enables switching between different Airbnb data sources without changing client code or tool schemas. Implements error handling, rate limiting, and retry logic at the server level.","intents":["Integrate Airbnb data without exposing scraping or API implementation details to clients","Switch between different Airbnb data sources (e.g., scraping to API) without breaking client code","Implement server-side caching and rate limiting to reduce load on Airbnb's backend","Handle authentication and data transformation transparently"],"best_for":["Teams building production travel systems that need reliable Airbnb data integration","Developers who want to decouple Airbnb data fetching from LLM agent logic","Systems that need to switch data sources or add fallback providers"],"limitations":["Data freshness depends on caching strategy — real-time pricing updates may not be available","Scraping-based implementations fragile to Airbnb UI changes — requires maintenance","Rate limiting may cause tool call failures during high-traffic periods","No built-in multi-region support — server must be deployed per region for low latency"],"requires":["Node.js 16+ runtime","Network access to Airbnb data source","Cache layer (optional but recommended for production)"],"input_types":["Search parameters and listing IDs from MCP tool calls"],"output_types":["Transformed JSON objects matching MCP tool output schemas"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":24,"verified":false,"data_access_risk":"high","permissions":["MCP client implementation (Claude Desktop, custom MCP host, or compatible LLM framework)","Node.js 16+ runtime for the MCP server process","Network access to Airbnb's data source (web or API endpoint)","MCP client compatible with tool calling","Node.js 16+ runtime","Valid Airbnb listing ID (typically 8-10 digit numeric ID)","MCP server implementation (Node.js)","MCP client that supports tool calling (Claude, custom LLM framework)","JSON schema knowledge for defining tool parameters","MCP client with multi-turn conversation support"],"failure_modes":["Depends on Airbnb's underlying data source stability — scraping-based implementations may break with UI changes","No authentication support — searches limited to public listing data only","Pagination may be limited by Airbnb's rate limiting or result set caps","No real-time pricing updates — cached or delayed pricing data possible","Requires valid Airbnb listing ID — no fuzzy matching or search-to-detail chaining built-in","Review data may be paginated or truncated — full review history may not be available","Pricing and availability calendar may be cached or stale","Host contact information not exposed — only public profile data available","Tool schema must be manually maintained — no automatic schema generation from backend code","Parameter validation is schema-based only — no runtime type coercion","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.2,"ecosystem":0.38999999999999996,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.904Z","last_scraped_at":"2026-05-03T14:23:38.468Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-openbnbmcp-server-airbnb","compare_url":"https://unfragile.ai/compare?artifact=npm-openbnbmcp-server-airbnb"}},"signature":"VWIFH37OuIt9XAG9tPMd3+mw6gDqRAraeHwtXGQosqSeQICiovXBIfPdlgqKJS2/8FSqYeQjyY+y2NqxKbQJCQ==","signedAt":"2026-06-21T18:53:05.192Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-openbnbmcp-server-airbnb","artifact":"https://unfragile.ai/npm-openbnbmcp-server-airbnb","verify":"https://unfragile.ai/api/v1/verify?slug=npm-openbnbmcp-server-airbnb","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}