{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github_mcp-borski-travel-hacking-toolkit","slug":"mcp-borski-travel-hacking-toolkit","name":"travel-hacking-toolkit","type":"repo","url":"https://github.com/borski/travel-hacking-toolkit","page_url":"https://unfragile.ai/mcp-borski-travel-hacking-toolkit","categories":["app-builders"],"tags":["award-flights","claude-code","flights","hotels","mcp","opencode","points-and-miles","skills","travel","travel-hacking"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github_mcp-borski-travel-hacking-toolkit__cap_0","uri":"capability://tool.use.integration.mcp.server.based.travel.data.integration","name":"mcp server-based travel data integration","description":"Exposes travel hacking data (award flight availability, points valuations, redemption opportunities) through the Model Context Protocol (MCP) server interface, enabling Claude and other AI agents to query and reason over real-time travel award information without direct API calls. Implements MCP resource and tool schemas to standardize access to heterogeneous travel data sources (airline loyalty programs, award flight databases, points marketplaces).","intents":["I want Claude to help me find the best award flight redemptions without manually checking airline websites","I need an AI agent to continuously monitor award flight availability and alert me to opportunities","I want to integrate travel hacking data into my custom AI workflow or agent"],"best_for":["AI developers building travel-focused agents or assistants","Teams integrating travel data into Claude Code or OpenCode workflows","Frequent flyers automating award flight discovery"],"limitations":["MCP server requires active maintenance to track airline API changes and loyalty program updates","Real-time award availability depends on upstream data source freshness — may lag 5-30 minutes behind actual inventory","No built-in caching layer — repeated queries to same routes may hit rate limits on underlying travel data APIs"],"requires":["Python 3.8+","MCP client implementation (Claude Code, OpenCode, or custom MCP runner)","Network access to configured travel data sources (airline APIs, award flight databases)"],"input_types":["structured queries (origin airport, destination airport, date range, cabin class)","natural language requests from Claude/AI agent"],"output_types":["structured award flight data (JSON with flight details, points cost, availability)","points valuation metrics","redemption opportunity rankings"],"categories":["tool-use-integration","travel-data-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_1","uri":"capability://code.generation.editing.claude.code.skill.injection.for.award.flight.optimization","name":"claude code skill injection for award flight optimization","description":"Provides drop-in Python skills and utilities that Claude Code can directly invoke to analyze award flight options, calculate points-per-mile valuations, and recommend optimal redemption strategies. Skills encapsulate domain logic for comparing cabin classes, routing options, and award availability across multiple airlines, allowing Claude to reason over travel hacking decisions with pre-built domain expertise.","intents":["I want Claude Code to automatically analyze award flight options and recommend the best redemption","I need Claude to calculate whether paying cash or using points is better for a specific route","I want Claude to help me plan a multi-leg award trip optimizing for points efficiency"],"best_for":["Claude Code users automating travel planning workflows","Developers extending Claude Code with travel domain expertise","Non-technical frequent flyers using Claude Code as a travel advisor"],"limitations":["Skills are tightly coupled to Claude Code runtime — not portable to other AI platforms without refactoring","Award flight data freshness depends on skill update frequency — manual updates required when airline programs change","No persistent state between Claude Code sessions — complex multi-step travel plans require re-context on each invocation"],"requires":["Claude Code environment (Anthropic's Claude Code IDE or compatible)","Python 3.8+ runtime in Claude Code","Access to travel hacking toolkit repository"],"input_types":["natural language travel queries from user","structured flight search parameters (origin, destination, dates, cabin)"],"output_types":["ranked award flight recommendations with points cost and value analysis","redemption strategy explanations","multi-leg itinerary suggestions"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_2","uri":"capability://tool.use.integration.opencode.skill.framework.integration","name":"opencode skill framework integration","description":"Provides travel hacking skills compatible with OpenCode's skill system, allowing OpenCode agents to access award flight data, points valuations, and redemption logic through OpenCode's native skill invocation mechanism. Implements OpenCode skill schema and lifecycle hooks to enable seamless skill discovery, parameter validation, and result formatting within OpenCode workflows.","intents":["I want to add travel hacking capabilities to my OpenCode agent without writing custom integrations","I need OpenCode to help me find award flights as part of a larger travel planning workflow","I want to reuse travel hacking logic across multiple OpenCode agents"],"best_for":["OpenCode developers building travel-focused agents","Teams standardizing on OpenCode for AI automation","Developers seeking portable skill implementations across multiple AI platforms"],"limitations":["OpenCode skill format may diverge from Claude Code format — dual maintenance required for feature parity","Skill parameter schemas must be manually kept in sync with underlying travel data API changes","No built-in versioning — breaking changes to skill signatures can break dependent agents"],"requires":["OpenCode environment or SDK","Python 3.8+","Travel hacking toolkit repository cloned or installed"],"input_types":["OpenCode skill invocation with structured parameters","natural language agent requests routed through OpenCode"],"output_types":["structured skill results (award flight options, points valuations)","formatted for OpenCode agent consumption"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_3","uri":"capability://search.retrieval.multi.airline.award.flight.availability.aggregation","name":"multi-airline award flight availability aggregation","description":"Aggregates real-time or near-real-time award flight availability data from multiple airline loyalty programs (United, American, Delta, etc.) into a unified query interface, normalizing different airline award charts, fuel surcharge policies, and availability calendars into comparable data structures. Uses airline API integrations or web scraping to fetch current inventory and presents results ranked by points efficiency and routing optimality.","intents":["I want to search for award flights across all major US airlines in one query","I need to find the cheapest award flight in points for a specific route","I want to see all available award flight options for a date range across multiple airlines"],"best_for":["Frequent flyers comparing award options across loyalty programs","Travel agents automating award flight searches for clients","Developers building travel search applications"],"limitations":["Airline APIs are not standardized — each airline requires custom integration logic, increasing maintenance burden","Some airlines actively block automated queries — toolkit may require rotating proxies or user-agent spoofing to maintain availability","Award availability is highly dynamic — data can become stale within minutes, requiring aggressive refresh rates that may trigger rate limits","Fuel surcharges and award chart changes are announced irregularly — manual updates required to maintain accuracy"],"requires":["Python 3.8+","API credentials or web scraping capability for target airlines","Network access to airline websites/APIs","Handling of potential IP blocking or rate limiting"],"input_types":["search parameters: origin airport code, destination airport code, departure date(s), cabin class, number of passengers","optional filters: preferred airlines, maximum points cost, routing preferences"],"output_types":["structured award flight results with: airline, flight number, departure/arrival times, points cost, fuel surcharges, cabin class, routing details","ranked by points efficiency (points per mile) or total cost"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_4","uri":"capability://data.processing.analysis.points.valuation.and.redemption.optimization","name":"points valuation and redemption optimization","description":"Calculates dynamic points valuations for different loyalty program currencies based on redemption opportunities, historical pricing, and market data. Implements algorithms to recommend optimal redemption strategies by comparing points-per-mile efficiency across different routes, cabin classes, and airlines, accounting for award chart variations and fuel surcharge policies. Provides valuation metrics that help users decide between cash and points payments.","intents":["I want to know if I should use points or pay cash for this flight","I need to calculate the effective value of my loyalty program points","I want to find the most points-efficient way to redeem for a specific destination"],"best_for":["Frequent flyers optimizing loyalty program spending","Travel hackers maximizing points efficiency","Financial planners valuing loyalty program assets"],"limitations":["Valuation models are heuristic-based and may not capture all market factors — actual redemption values can vary significantly","Historical pricing data may not reflect current market conditions, especially post-pandemic or during airline capacity constraints","Fuel surcharge policies change frequently — valuation models require regular updates to remain accurate","No account for personal preferences (airline, routing, schedule) — optimization is purely financial"],"requires":["Python 3.8+","Historical award flight pricing data (internal or from third-party sources)","Current airline award charts and fuel surcharge policies"],"input_types":["loyalty program currency (e.g., 'United miles', 'American AAdvantage points')","optional: specific redemption route or flight details"],"output_types":["valuation metrics: cents per point, points per mile for specific routes","redemption recommendations ranked by efficiency","cash vs points comparison for specific flights"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_5","uri":"capability://memory.knowledge.loyalty.program.account.integration.and.balance.tracking","name":"loyalty program account integration and balance tracking","description":"Integrates with airline and hotel loyalty program accounts to fetch real-time points/miles balances, elite status, and account details. Implements secure credential storage and OAuth/API authentication to loyalty programs, enabling automated balance monitoring and integration with award flight search workflows. Tracks balance changes over time to detect earning opportunities and expiration risks.","intents":["I want Claude to check my loyalty program balances and tell me what I can afford to redeem","I need to monitor my points balance across multiple airlines to track earning progress","I want alerts when my points are about to expire"],"best_for":["Frequent flyers automating loyalty account monitoring","AI agents that need real-time points balances for redemption recommendations","Travel hackers tracking points across multiple programs"],"limitations":["Most airlines do not offer official APIs for account access — integration requires web scraping or third-party account aggregation services, which are fragile and prone to breakage","Credential storage introduces security risk — requires careful handling of sensitive login information","Account access may trigger fraud detection or account lockouts if queries appear suspicious","No standardized format across loyalty programs — each program requires custom parsing logic"],"requires":["Python 3.8+","Loyalty program credentials (username/password or OAuth tokens)","Secure credential storage mechanism (environment variables, encrypted vault, or third-party service)","Network access to loyalty program websites/APIs"],"input_types":["loyalty program identifiers (airline, account number or username)","optional: credentials (if not pre-configured)"],"output_types":["structured account data: points/miles balance, elite status, account expiration dates","balance history (if tracking enabled)","expiration warnings"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_6","uri":"capability://planning.reasoning.multi.leg.award.trip.planning.and.routing.optimization","name":"multi-leg award trip planning and routing optimization","description":"Analyzes complex multi-leg award trips to optimize routing, minimize points cost, and maximize value. Implements graph-based routing algorithms to find efficient connections across multiple airlines and loyalty programs, accounting for award chart variations, fuel surcharges, and stopover policies. Recommends itineraries that balance points efficiency with schedule preferences and routing flexibility.","intents":["I want to plan a round-the-world trip using award flights and minimize total points cost","I need to find the best routing for a multi-city trip across different airlines","I want to understand stopover policies and how they affect my trip planning"],"best_for":["Travel hackers planning complex multi-leg award trips","Frequent flyers optimizing long-haul redemptions","AI agents recommending itineraries to users"],"limitations":["Routing optimization is NP-hard — algorithm complexity grows exponentially with number of legs, limiting practical trip complexity","Stopover and open-jaw policies vary significantly by airline and award chart — rules engine requires constant maintenance","Award availability is dynamic — optimal routing may become unavailable by the time user attempts to book","No account for personal preferences (schedule, airline, routing) — optimization is purely financial"],"requires":["Python 3.8+","Multi-airline award chart data","Routing optimization library (e.g., networkx for graph algorithms)"],"input_types":["trip parameters: origin, destinations (multiple), dates, cabin class, number of passengers","optional: preferred airlines, routing constraints, schedule preferences"],"output_types":["ranked itineraries with: routing details, total points cost, fuel surcharges, schedule, stopover/open-jaw usage","explanation of routing logic and trade-offs"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_7","uri":"capability://automation.workflow.award.chart.change.detection.and.policy.tracking","name":"award chart change detection and policy tracking","description":"Monitors airline award charts, fuel surcharge policies, and loyalty program rules for changes, automatically detecting updates and alerting users to changes that affect redemption value. Implements periodic scraping or API polling of airline websites to detect award chart modifications, fuel surcharge adjustments, and policy changes, comparing against historical snapshots to identify deltas.","intents":["I want to be notified when an airline changes its award chart or fuel surcharges","I need to track how award chart changes affect my redemption options","I want to know when award charts become more or less valuable"],"best_for":["Travel hackers monitoring award chart changes for opportunities","Frequent flyers tracking policy changes that affect their accounts","Teams maintaining travel hacking tools that depend on accurate award chart data"],"limitations":["Airlines do not publish award chart change notifications — detection requires continuous scraping, which is resource-intensive and fragile","Change detection is heuristic-based — may miss subtle policy changes or generate false positives","Fuel surcharge changes are announced irregularly and sometimes retroactively — detection lag is unavoidable","No standardized format for award chart publication — each airline requires custom parsing logic"],"requires":["Python 3.8+","Scheduled task runner (cron, APScheduler, or cloud scheduler)","Storage for historical award chart snapshots","Network access to airline websites"],"input_types":["target airlines to monitor","optional: notification preferences (email, webhook, etc.)"],"output_types":["change notifications with: airline, policy changed, old value, new value, effective date","impact analysis: routes affected, value change"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-borski-travel-hacking-toolkit__cap_8","uri":"capability://text.generation.language.natural.language.travel.query.understanding.and.routing","name":"natural language travel query understanding and routing","description":"Parses natural language travel queries from users (e.g., 'I want to fly from NYC to Tokyo in business class next month') and routes them to appropriate travel hacking tools and data sources. Implements intent classification and entity extraction to identify travel parameters (origin, destination, dates, cabin class, constraints), then orchestrates downstream tools to fulfill the request. Handles ambiguous or incomplete queries by asking clarifying questions.","intents":["I want to ask Claude in natural language about award flights without specifying technical parameters","I need Claude to understand my travel preferences and constraints from conversational context","I want Claude to ask follow-up questions when my travel request is ambiguous"],"best_for":["Non-technical frequent flyers using Claude Code or OpenCode for travel planning","AI agents that need to understand user travel intent from natural language","Conversational travel assistants"],"limitations":["Intent classification is probabilistic — may misinterpret complex or ambiguous queries","Entity extraction may fail on non-standard airport codes or date formats","No account for implicit constraints (e.g., 'I prefer direct flights' requires additional context)","Requires training data or fine-tuning for domain-specific language patterns"],"requires":["Python 3.8+","NLP library (spaCy, NLTK, or LLM-based extraction)","Travel domain entity definitions (airports, airlines, cabin classes)"],"input_types":["natural language travel queries (text)"],"output_types":["structured travel parameters: origin, destination, dates, cabin class, constraints","confidence scores for extracted entities","clarifying questions for ambiguous inputs"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Python 3.8+","MCP client implementation (Claude Code, OpenCode, or custom MCP runner)","Network access to configured travel data sources (airline APIs, award flight databases)","Claude Code environment (Anthropic's Claude Code IDE or compatible)","Python 3.8+ runtime in Claude Code","Access to travel hacking toolkit repository","OpenCode environment or SDK","Travel hacking toolkit repository cloned or installed","API credentials or web scraping capability for target airlines","Network access to airline websites/APIs"],"failure_modes":["MCP server requires active maintenance to track airline API changes and loyalty program updates","Real-time award availability depends on upstream data source freshness — may lag 5-30 minutes behind actual inventory","No built-in caching layer — repeated queries to same routes may hit rate limits on underlying travel data APIs","Skills are tightly coupled to Claude Code runtime — not portable to other AI platforms without refactoring","Award flight data freshness depends on skill update frequency — manual updates required when airline programs change","No persistent state between Claude Code sessions — complex multi-step travel plans require re-context on each invocation","OpenCode skill format may diverge from Claude Code format — dual maintenance required for feature parity","Skill parameter schemas must be manually kept in sync with underlying travel data API changes","No built-in versioning — breaking changes to skill signatures can break dependent agents","Airline APIs are not standardized — each airline requires custom integration logic, increasing maintenance burden","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3372896757114059,"quality":0.43,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.064Z","last_scraped_at":"2026-05-03T14:23:44.761Z","last_commit":"2026-05-02T22:24:59Z"},"community":{"stars":464,"forks":38,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-borski-travel-hacking-toolkit","compare_url":"https://unfragile.ai/compare?artifact=mcp-borski-travel-hacking-toolkit"}},"signature":"HPRvMG5sEdRyp+nyttGMPsn25OX1mj3ZdchEJKtcPEsdAJAG4/+gWVfA6siZXzsL2okxjOp9IHmBVJR8I/B/AQ==","signedAt":"2026-06-21T09:26:53.799Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-borski-travel-hacking-toolkit","artifact":"https://unfragile.ai/mcp-borski-travel-hacking-toolkit","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-borski-travel-hacking-toolkit","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"}}