{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_ahump20-live-sports-scoreboard-api","slug":"ahump20-live-sports-scoreboard-api","name":"live-sports-scoreboard-api","type":"mcp","url":"https://github.com/ahump20/live-sports-scoreboard-api","page_url":"https://unfragile.ai/ahump20-live-sports-scoreboard-api","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","smithery:ahump20/live-sports-scoreboard-api"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_0","uri":"capability://tool.use.integration.live.sports.score.retrieval.via.mcp","name":"live-sports-score-retrieval-via-mcp","description":"Exposes real-time sports scoreboard data through the Model Context Protocol (MCP) standard, allowing Claude and other MCP-compatible clients to query live game scores, team statistics, and match results without direct API calls. Implements MCP resource and tool handlers that translate incoming requests into structured queries against a sports data backend, returning JSON-formatted game state with scores, timestamps, and team metadata.","intents":["I want Claude to fetch live sports scores and embed them in my conversation without me manually checking a sports website","I need to build an AI agent that can answer questions about current game scores and standings in real-time","I want to integrate live sports data into my MCP-based application stack without managing separate API credentials"],"best_for":["AI application developers building Claude-integrated sports analytics tools","Teams building MCP servers that need to compose multiple data sources including live sports","Non-technical users wanting Claude to have access to live sports information via MCP"],"limitations":["Depends on upstream sports data provider availability and rate limits — if the underlying API is down, scoreboard data becomes stale","No built-in caching layer specified — repeated queries for the same game may hit rate limits or incur latency","Limited to sports leagues/data sources supported by the underlying provider — niche sports or regional leagues may not be available","MCP protocol overhead adds ~50-200ms per request compared to direct API calls due to serialization and context passing"],"requires":["MCP client compatible with the server implementation (Claude desktop, Cline, or other MCP-aware tools)","Network connectivity to the upstream sports data provider","Proper MCP server configuration and initialization in the client environment"],"input_types":["text (sport name, team name, league identifier)","structured parameters (date range, team filters, score thresholds)"],"output_types":["JSON (game objects with scores, timestamps, team data)","structured text (formatted score summaries for display)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_1","uri":"capability://tool.use.integration.mcp.resource.handler.for.scoreboard.endpoints","name":"mcp-resource-handler-for-scoreboard-endpoints","description":"Implements MCP resource handlers that expose scoreboard data as queryable endpoints, allowing clients to request specific games, teams, or leagues through a standardized resource URI pattern. The server registers resource handlers that parse incoming MCP requests, validate parameters, and return structured scoreboard data formatted according to MCP resource response schemas.","intents":["I want to query specific games or teams using a consistent MCP resource interface rather than learning a custom API","I need my MCP client to discover available scoreboard resources and their schemas dynamically","I want to compose this sports data server with other MCP servers in a unified context"],"best_for":["MCP server developers building composite data platforms","Claude users who want standardized resource access patterns across multiple data sources","Teams implementing MCP-based data federation architectures"],"limitations":["Resource discovery is limited to MCP's built-in introspection — no custom schema documentation beyond what the MCP protocol provides","Stateless resource handlers mean no session-based filtering or personalization — each request is independent","Resource URI patterns are fixed at server startup — dynamic resource registration is not supported"],"requires":["MCP server framework (likely Node.js/TypeScript based on GitHub context)","Understanding of MCP resource URI conventions and response schemas","MCP client that supports resource queries"],"input_types":["MCP resource URIs (e.g., 'scoreboard://games/nfl/2024-01-15')","query parameters (team filters, date ranges)"],"output_types":["JSON resources (game objects, team standings, league data)","MCP resource metadata (schemas, descriptions)"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_2","uri":"capability://tool.use.integration.mcp.tool.calling.for.score.queries","name":"mcp-tool-calling-for-score-queries","description":"Registers MCP tools that allow clients to invoke parameterized queries for sports scores, such as 'get_game_score(team, date)' or 'get_standings(league)'. The server defines tool schemas with input validation, executes the queries against the sports data backend, and returns results in a format suitable for LLM processing and display.","intents":["I want Claude to call a tool to fetch the latest score for a specific team without me specifying the exact API endpoint","I need parameterized score queries that Claude can invoke with natural language intent (e.g., 'What's the score of the Lakers game?')","I want tool calling with input validation to prevent invalid queries from reaching the backend"],"best_for":["Developers building Claude agents that need to answer sports questions conversationally","Non-technical users who want Claude to fetch sports data via natural language","Teams building multi-tool MCP agents where sports data is one of many available tools"],"limitations":["Tool schema must be predefined at server startup — dynamic tool registration based on available leagues/sports is not supported","Input validation is schema-based only — complex business logic (e.g., 'get the most recent game for this team') requires the client to handle disambiguation","Tool calling adds latency due to LLM reasoning overhead — Claude must decide which tool to call before the query executes"],"requires":["MCP client that supports tool calling (Claude, Cline, etc.)","Tool schema definitions in JSON Schema format","Backend sports data API with query support"],"input_types":["tool parameters (team name, league, date, player name)","natural language intent (processed by Claude before tool invocation)"],"output_types":["JSON (score data, player stats, standings)","formatted text (human-readable score summaries)"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_3","uri":"capability://tool.use.integration.real.time.score.update.streaming","name":"real-time-score-update-streaming","description":"Provides mechanisms for clients to receive live score updates as games progress, likely through MCP's notification or subscription patterns. The server monitors upstream sports data sources for score changes and pushes updates to subscribed clients, enabling real-time scoreboard displays without polling.","intents":["I want my Claude conversation to automatically update with new scores as games progress without me asking repeatedly","I need a real-time sports dashboard that reflects live game state changes instantly","I want to build an agent that reacts to score changes (e.g., alerts when a team scores)"],"best_for":["Developers building real-time sports dashboards or live commentary agents","Teams needing low-latency score updates for time-sensitive applications","Users who want Claude to maintain awareness of ongoing games without manual refreshes"],"limitations":["Streaming updates depend on upstream provider's update frequency — if the sports data source updates every 30 seconds, client updates are delayed by that interval","MCP protocol may not have native streaming support — implementation may require polling with short intervals, adding server load","Subscription state is not persisted — client reconnections require re-subscribing to score updates","No built-in filtering — clients receive all score updates and must filter locally, potentially wasting bandwidth"],"requires":["MCP client with subscription/notification support","Persistent connection between client and server (WebSocket or similar)","Upstream sports data provider with real-time or near-real-time updates"],"input_types":["subscription parameters (games, teams, leagues to monitor)"],"output_types":["JSON notifications (score deltas, game state changes)","event streams (game started, score updated, game ended)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_4","uri":"capability://data.processing.analysis.multi.sport.league.data.aggregation","name":"multi-sport-league-data-aggregation","description":"Aggregates scoreboard data from multiple sports leagues (NFL, NBA, MLB, NHL, soccer, etc.) into a unified query interface, allowing clients to request scores across different sports without managing separate API connections. The server normalizes league-specific data formats into a common schema and routes queries to the appropriate backend provider.","intents":["I want to ask Claude about scores from multiple sports (e.g., 'What's happening in sports today?') without specifying which league","I need a unified API that handles NFL, NBA, and soccer scores without managing three separate integrations","I want to build a sports agent that can answer questions about any sport without hardcoding league-specific logic"],"best_for":["Developers building general-purpose sports agents or dashboards","Non-technical users who want Claude to answer sports questions across all major leagues","Teams building multi-sport platforms that need a single integration point"],"limitations":["Data freshness varies by league — some sports update scores in real-time while others batch updates, creating inconsistent latency","Schema normalization may lose league-specific details (e.g., NFL play-by-play data, NBA player stats) — clients need custom handling for detailed league data","Upstream provider coverage is limited to supported leagues — niche sports or international leagues may not be available","Query routing adds latency as the server determines which backend provider to query based on league/sport parameters"],"requires":["Integrations with multiple sports data providers (ESPN API, official league APIs, etc.)","Unified schema definition that maps across different league data structures","MCP client that can handle multi-sport queries"],"input_types":["sport/league identifiers (NFL, NBA, MLB, etc.)","team names or league-agnostic queries (e.g., 'all games today')"],"output_types":["normalized JSON (games, scores, standings in a common format)","league-specific metadata (league name, season, playoff status)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_5","uri":"capability://data.processing.analysis.team.and.player.metadata.enrichment","name":"team-and-player-metadata-enrichment","description":"Augments raw score data with team and player metadata such as logos, team colors, player names, statistics, and historical records. The server caches or fetches this metadata from upstream sources and includes it in score responses, enabling rich UI rendering and contextual information without additional client queries.","intents":["I want Claude to provide team logos and colors along with scores for better visual presentation","I need player names and stats to be included in score responses so I can ask follow-up questions about specific players","I want to display team records and playoff status alongside live scores"],"best_for":["Developers building rich sports dashboards or UI applications","Teams needing contextual metadata for sports data analysis or reporting","Claude users who want detailed team/player information alongside scores"],"limitations":["Metadata caching adds complexity — stale metadata (e.g., outdated player rosters) may be served if cache TTL is too long","Metadata enrichment increases response payload size, potentially exceeding MCP message size limits for large queries","Player statistics may lag behind live scores — historical stats are updated less frequently than game scores","Metadata availability varies by league — some leagues provide rich metadata while others offer minimal team/player information"],"requires":["Metadata sources (team databases, player registries, official league APIs)","Caching layer (Redis, in-memory cache) for performance","Schema definitions for metadata fields (logos, colors, stats, records)"],"input_types":["team identifiers, player names, league identifiers"],"output_types":["enriched JSON (scores with team logos, colors, player stats, records)","metadata objects (team info, player profiles)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_6","uri":"capability://data.processing.analysis.league.standings.and.statistics.queries","name":"league-standings-and-statistics-queries","description":"Provides queries for league standings, team statistics, and historical records beyond individual game scores. The server aggregates season-long data (wins/losses, point differentials, playoff seeding) and serves it through MCP tools/resources, enabling clients to ask questions about team rankings, playoff scenarios, and statistical comparisons.","intents":["I want Claude to tell me the current standings and playoff seeding for a league","I need to compare team statistics (wins, losses, point differential) across the season","I want to ask about historical records and statistical milestones (e.g., 'Is this team on pace for a record season?')"],"best_for":["Sports analysts and journalists building AI-powered reporting tools","Developers creating sports trivia or statistics agents","Teams building comprehensive sports platforms that need standings and historical context"],"limitations":["Standings data is only as current as the last game update — standings may lag behind live scores by minutes or hours","Historical statistics are immutable once a season ends — in-season stats require frequent updates to stay current","Playoff scenarios and 'magic number' calculations require complex business logic that may not be implemented","Statistical comparisons across leagues are difficult due to different rules and scoring systems"],"requires":["Upstream data source with season-long standings and statistics","Aggregation logic to compute standings from individual game results","Caching for frequently-accessed standings data"],"input_types":["league identifier, season year, team name"],"output_types":["JSON standings (team records, win-loss, playoff seeding)","statistical summaries (point differential, strength of schedule, statistical leaders)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_ahump20-live-sports-scoreboard-api__cap_7","uri":"capability://search.retrieval.schedule.and.upcoming.games.lookup","name":"schedule-and-upcoming-games-lookup","description":"Provides queries for upcoming games, schedules, and game times across leagues. The server fetches schedule data from upstream sources and allows clients to ask about future matchups, game times, and scheduling information without manual calendar management.","intents":["I want Claude to tell me when the next game is for a specific team","I need to know the full schedule for a team or league for planning purposes","I want to ask about upcoming matchups and game times in my timezone"],"best_for":["Developers building sports scheduling or calendar applications","Claude users who want to know upcoming game times without checking a website","Teams building sports agents that need to understand future matchups"],"limitations":["Schedule data is static until officially released — early-season schedules may not be available","Timezone handling is complex — the server must convert game times to client timezones, which requires timezone information from clients","Schedule changes (postponements, rescheduling) require real-time updates — the server must monitor for schedule changes and invalidate cached data","Preseason and playoff schedules may not be available until officially announced"],"requires":["Upstream schedule data source (official league APIs, ESPN, etc.)","Schedule caching with invalidation logic for changes","Timezone handling for client-specific time conversion"],"input_types":["team identifier, league, date range"],"output_types":["JSON schedule (games, times, opponents, venues)","formatted text (human-readable game times)"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":28,"verified":false,"data_access_risk":"high","permissions":["MCP client compatible with the server implementation (Claude desktop, Cline, or other MCP-aware tools)","Network connectivity to the upstream sports data provider","Proper MCP server configuration and initialization in the client environment","MCP server framework (likely Node.js/TypeScript based on GitHub context)","Understanding of MCP resource URI conventions and response schemas","MCP client that supports resource queries","MCP client that supports tool calling (Claude, Cline, etc.)","Tool schema definitions in JSON Schema format","Backend sports data API with query support","MCP client with subscription/notification support"],"failure_modes":["Depends on upstream sports data provider availability and rate limits — if the underlying API is down, scoreboard data becomes stale","No built-in caching layer specified — repeated queries for the same game may hit rate limits or incur latency","Limited to sports leagues/data sources supported by the underlying provider — niche sports or regional leagues may not be available","MCP protocol overhead adds ~50-200ms per request compared to direct API calls due to serialization and context passing","Resource discovery is limited to MCP's built-in introspection — no custom schema documentation beyond what the MCP protocol provides","Stateless resource handlers mean no session-based filtering or personalization — each request is independent","Resource URI patterns are fixed at server startup — dynamic resource registration is not supported","Tool schema must be predefined at server startup — dynamic tool registration based on available leagues/sports is not supported","Input validation is schema-based only — complex business logic (e.g., 'get the most recent game for this team') requires the client to handle disambiguation","Tool calling adds latency due to LLM reasoning overhead — Claude must decide which tool to call before the query executes","builder identity is not verified yet","no observed match outcomes 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