{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-twelve-data","slug":"twelve-data","name":"Twelve Data","type":"mcp","url":"https://github.com/twelvedata/mcp","page_url":"https://unfragile.ai/twelve-data","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-twelve-data__cap_0","uri":"capability://tool.use.integration.real.time.market.data.streaming.via.mcp.protocol","name":"real-time market data streaming via mcp protocol","description":"Exposes Twelve Data's real-time quote APIs through the Model Context Protocol (MCP), allowing AI agents to subscribe to live price feeds, bid-ask spreads, and volume data across equities, forex, crypto, and commodities. Implements MCP resource handlers that map financial data endpoints to standardized tool schemas, enabling LLMs to request current market snapshots without direct HTTP knowledge.","intents":["I need my AI agent to fetch the current price of a stock or crypto asset in real-time","I want to build a trading bot that reacts to live market data within an LLM conversation","I need to integrate live financial quotes into my agent's decision-making loop"],"best_for":["AI agent builders creating financial advisory or trading assistants","LLM application developers needing live market context without API management overhead","Teams building MCP-compatible AI systems that require financial data feeds"],"limitations":["Rate limits depend on Twelve Data subscription tier; free tier has restricted quote frequency","Latency adds ~100-500ms per request depending on Twelve Data backend load","Real-time streaming requires active MCP connection; no built-in reconnection or fallback logic","No local caching layer — every agent query hits the Twelve Data API directly"],"requires":["Twelve Data API key (free or paid tier)","MCP-compatible client (Claude Desktop, custom MCP host, or compatible LLM framework)","Network connectivity to Twelve Data API endpoints","Python 3.8+ or Node.js 16+ (depending on MCP server implementation)"],"input_types":["symbol string (e.g., 'AAPL', 'EURUSD', 'BTC/USD')","optional parameters: exchange, currency, type (stock/forex/crypto/etf)"],"output_types":["JSON object with price, bid, ask, volume, timestamp","structured market data ready for agent reasoning"],"categories":["tool-use-integration","search-retrieval","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-twelve-data__cap_1","uri":"capability://data.processing.analysis.historical.ohlcv.time.series.retrieval.with.configurable.intervals","name":"historical ohlcv time-series retrieval with configurable intervals","description":"Provides access to Twelve Data's historical candlestick data (open, high, low, close, volume) across multiple timeframes (1-minute to monthly) for backtesting, analysis, and historical context in agent reasoning. Implements MCP tools that accept symbol, date range, and interval parameters, returning structured time-series arrays suitable for technical analysis or LLM context windows.","intents":["I need historical price data for a stock to analyze trends within my agent's reasoning","I want to backtest a trading strategy by fetching 6 months of daily OHLCV data","I need to provide my LLM with historical context (e.g., 'prices were at X on date Y') for informed decisions"],"best_for":["Quantitative analysts building LLM-powered backtesting systems","Financial AI agents that need historical context for decision-making","Developers creating financial dashboards or reporting tools powered by LLMs"],"limitations":["Historical data depth varies by subscription tier; free tier limited to ~1 year of data","Intraday data (1-5 minute intervals) only available for recent periods (typically last 30-90 days)","Large date ranges (e.g., 10 years of daily data) may return paginated responses requiring iteration","No built-in aggregation — requesting 1-minute data for 1 year will return ~250k+ candles, potentially exceeding context window limits"],"requires":["Twelve Data API key with historical data access","MCP client supporting tool parameters (symbol, start_date, end_date, interval)","Python 3.8+ or Node.js 16+","Sufficient memory to handle large time-series arrays in agent context"],"input_types":["symbol (string, e.g., 'AAPL')","start_date (ISO 8601 format, e.g., '2023-01-01')","end_date (ISO 8601 format)","interval (enum: '1min', '5min', '15min', '30min', '45min', '1h', '4h', '1day', '1week', '1month')"],"output_types":["JSON array of candlestick objects: [{datetime, open, high, low, close, volume}, ...]","CSV or JSON export formats for downstream analysis"],"categories":["data-processing-analysis","tool-use-integration","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-twelve-data__cap_2","uri":"capability://search.retrieval.multi.asset.symbol.lookup.and.metadata.resolution","name":"multi-asset symbol lookup and metadata resolution","description":"Implements MCP tools for searching and resolving financial instrument symbols across asset classes (stocks, ETFs, forex pairs, cryptocurrencies, indices) using Twelve Data's symbol search API. Returns standardized metadata including ISIN, exchange, country, and asset type, enabling agents to disambiguate user queries (e.g., 'Apple' → 'AAPL' on NASDAQ) and validate symbols before data requests.","intents":["I need to convert a company name ('Apple') into its ticker symbol for data lookups","I want my agent to find all available symbols matching a partial search (e.g., 'tech stocks starting with A')","I need to validate that a user-provided symbol exists and get its exchange and asset type"],"best_for":["Conversational AI agents handling natural-language financial queries","Financial search and discovery tools powered by LLMs","Multi-asset portfolio management systems needing symbol disambiguation"],"limitations":["Search results limited to Twelve Data's supported instruments; some regional or delisted symbols may not be available","Fuzzy matching quality depends on Twelve Data's backend implementation; exact matches are more reliable than partial searches","No caching of symbol metadata — repeated searches for the same company will hit the API","Search results may return multiple matches (e.g., multiple 'Apple' entities); agent must disambiguate by exchange or asset type"],"requires":["Twelve Data API key","MCP client supporting string search parameters","Python 3.8+ or Node.js 16+"],"input_types":["search_query (string, e.g., 'Apple', 'AAPL', 'tech stocks')","optional filters: asset_type (stock/etf/forex/crypto/index), exchange, country"],"output_types":["JSON array of symbol objects: [{symbol, name, exchange, asset_type, country, isin}, ...]","structured metadata for agent disambiguation logic"],"categories":["search-retrieval","tool-use-integration","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-twelve-data__cap_3","uri":"capability://data.processing.analysis.technical.indicators.computation.on.demand","name":"technical indicators computation on-demand","description":"Exposes Twelve Data's technical analysis API through MCP, enabling agents to request computed indicators (SMA, EMA, RSI, MACD, Bollinger Bands, ATR, etc.) for any symbol and timeframe without implementing indicator logic. Returns indicator values aligned with historical candles, allowing agents to reason about momentum, trend, and volatility in natural language.","intents":["I want my trading agent to evaluate RSI and MACD for a stock to decide entry/exit points","I need to compute a 20-day moving average for a cryptocurrency to assess trend strength","I want to check if a stock is overbought (RSI > 70) or oversold (RSI < 30) before recommending a trade"],"best_for":["AI-powered trading bots and financial advisors","Technical analysis systems where LLMs interpret indicator signals","Agents that need to reason about market momentum and trend without external libraries"],"limitations":["Indicator computation happens server-side; agents cannot customize indicator parameters beyond what Twelve Data exposes","Some advanced indicators (e.g., custom oscillators) may not be available; limited to standard TA-Lib indicators","Indicator values depend on historical data availability; short symbols with limited history may have sparse indicator output","No real-time indicator updates — agents must re-request to get latest values as new candles form"],"requires":["Twelve Data API key with technical indicators access","MCP client supporting indicator parameter specification","Python 3.8+ or Node.js 16+","Sufficient historical data for the requested indicator (e.g., 200 candles for 200-period SMA)"],"input_types":["symbol (string)","interval (enum: '1min' to '1month')","indicator_type (enum: 'sma', 'ema', 'rsi', 'macd', 'bbands', 'atr', 'adx', 'stoch', etc.)","optional parameters: period, fast_period, slow_period (indicator-specific)"],"output_types":["JSON array of indicator values: [{datetime, value}, ...] or [{datetime, macd, signal, histogram}, ...] for multi-line indicators","structured data aligned with historical candles for agent reasoning"],"categories":["data-processing-analysis","tool-use-integration","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-twelve-data__cap_4","uri":"capability://search.retrieval.earnings.and.corporate.events.calendar.access","name":"earnings and corporate events calendar access","description":"Provides MCP tools to query Twelve Data's corporate events API, returning upcoming earnings dates, dividend announcements, stock splits, and other material events for equities. Agents can check event calendars to contextualize market movements or avoid trading around high-volatility events.","intents":["I need to check if a stock has earnings coming up before recommending a trade","I want to see the dividend payment date and amount for a stock in my portfolio","I need to identify stocks with upcoming stock splits or corporate actions that might affect pricing"],"best_for":["Fundamental analysis agents that incorporate corporate events into decision-making","Portfolio management systems that flag upcoming earnings or dividend dates","Risk management systems that avoid trading around high-impact events"],"limitations":["Event data limited to equities; forex, crypto, and commodities have minimal or no event calendars","Forward-looking data (future events) may have lower accuracy than historical events; dates can change","Not all corporate actions are captured; smaller companies or regional exchanges may have incomplete event data","No real-time event updates — agents must re-query to detect newly announced events"],"requires":["Twelve Data API key with corporate events access","MCP client supporting date range parameters","Python 3.8+ or Node.js 16+"],"input_types":["symbol (string, e.g., 'AAPL')","optional: start_date, end_date (ISO 8601 format) to filter events by date range","optional: event_type filter (earnings, dividend, split, etc.)"],"output_types":["JSON array of event objects: [{date, type, description, value}, ...]","structured event metadata for agent filtering and reasoning"],"categories":["search-retrieval","tool-use-integration","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-twelve-data__cap_5","uri":"capability://data.processing.analysis.currency.conversion.and.forex.pair.data","name":"currency conversion and forex pair data","description":"Exposes Twelve Data's forex API through MCP, enabling agents to convert between currencies, fetch real-time and historical forex pair rates, and access bid-ask spreads for currency trading. Supports major pairs (EUR/USD, GBP/USD) and exotic pairs, with configurable intervals for technical analysis on currency movements.","intents":["I need to convert a price from USD to EUR for a user in Europe","I want my agent to monitor GBP/USD for trading opportunities","I need historical forex data to analyze currency trends for international portfolio hedging"],"best_for":["International financial advisors and portfolio managers","Forex trading bots and currency arbitrage systems","Global e-commerce or fintech platforms needing real-time currency conversion"],"limitations":["Forex data subject to market hours; some exotic pairs may have lower liquidity and wider spreads","Conversion rates are point-in-time; agents cannot guarantee historical conversion accuracy for past transactions","Bid-ask spreads vary by broker and liquidity; Twelve Data spreads may differ from actual trading execution","No leverage or margin trading data; agents cannot assess margin requirements or funding costs"],"requires":["Twelve Data API key with forex access","MCP client supporting currency pair parameters","Python 3.8+ or Node.js 16+"],"input_types":["from_currency (string, e.g., 'USD')","to_currency (string, e.g., 'EUR')","optional: amount (number for conversion calculation)","optional: pair (string, e.g., 'EUR/USD') for direct pair queries"],"output_types":["JSON object with exchange rate, bid, ask, timestamp","conversion result (amount * rate) for currency conversion","historical time-series for forex pairs"],"categories":["data-processing-analysis","tool-use-integration","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-twelve-data__cap_6","uri":"capability://data.processing.analysis.cryptocurrency.and.digital.asset.data.access","name":"cryptocurrency and digital asset data access","description":"Provides MCP tools for querying Twelve Data's crypto API, including real-time prices, historical OHLCV data, and market cap information for cryptocurrencies across multiple exchanges. Agents can track crypto portfolios, analyze price movements, and reason about crypto market trends without external crypto-specific APIs.","intents":["I need to fetch the current price of Bitcoin and Ethereum for a portfolio dashboard","I want my agent to analyze historical Bitcoin price data to identify support/resistance levels","I need to compare crypto prices across exchanges (e.g., BTC/USD on Coinbase vs Kraken)"],"best_for":["Crypto portfolio trackers and wealth management agents","Crypto trading bots and market analysis systems","Multi-asset agents that need to treat crypto alongside traditional equities"],"limitations":["Crypto market operates 24/7 with high volatility; price data can be stale if not refreshed frequently","Exchange coverage varies; not all crypto exchanges are supported; some altcoins may have limited data","Crypto data quality depends on exchange liquidity; low-volume coins may have sparse or unreliable price history","No on-chain data (transaction volume, wallet addresses, smart contract interactions); limited to price and market cap"],"requires":["Twelve Data API key with crypto access","MCP client supporting crypto symbol parameters (e.g., 'BTC/USD')","Python 3.8+ or Node.js 16+"],"input_types":["symbol (string, e.g., 'BTC/USD', 'ETH/EUR')","optional: exchange filter (Coinbase, Kraken, Binance, etc.)","optional: interval for historical data (1min to 1month)"],"output_types":["JSON object with price, market cap, 24h change, volume","historical OHLCV time-series for crypto pairs","structured market data for agent reasoning"],"categories":["data-processing-analysis","tool-use-integration","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-twelve-data__cap_7","uri":"capability://tool.use.integration.mcp.protocol.integration.and.tool.schema.abstraction","name":"mcp protocol integration and tool schema abstraction","description":"Implements the Model Context Protocol (MCP) server architecture, exposing Twelve Data financial APIs as standardized MCP tools with JSON schema definitions. Handles authentication (API key management), request/response serialization, error handling, and tool discovery, allowing any MCP-compatible client (Claude Desktop, custom LLM frameworks) to invoke financial data tools without custom integration code.","intents":["I want to use Twelve Data APIs in Claude Desktop without writing custom code","I need to integrate Twelve Data into my custom LLM framework that supports MCP","I want my AI agent to have access to financial data tools with automatic schema validation"],"best_for":["LLM application developers using MCP-compatible frameworks","Teams standardizing on MCP for AI tool integration","Non-technical users wanting to add financial data to Claude Desktop"],"limitations":["MCP protocol overhead adds ~50-100ms per tool invocation compared to direct API calls","Tool discovery and schema validation happen at runtime; no compile-time type checking","Error handling depends on MCP client implementation; some clients may not surface detailed error messages","Authentication is API-key based; no OAuth or multi-user session management built-in"],"requires":["Twelve Data API key","MCP-compatible client (Claude Desktop, custom MCP host, or compatible LLM framework)","Python 3.8+ or Node.js 16+ for running the MCP server","Network connectivity between MCP client and server"],"input_types":["MCP tool invocation with JSON parameters matching tool schema","API key for Twelve Data authentication"],"output_types":["JSON-RPC responses with tool results","structured error messages for failed requests"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":29,"verified":false,"data_access_risk":"high","permissions":["Twelve Data API key (free or paid tier)","MCP-compatible client (Claude Desktop, custom MCP host, or compatible LLM framework)","Network connectivity to Twelve Data API endpoints","Python 3.8+ or Node.js 16+ (depending on MCP server implementation)","Twelve Data API key with historical data access","MCP client supporting tool parameters (symbol, start_date, end_date, interval)","Python 3.8+ or Node.js 16+","Sufficient memory to handle large time-series arrays in agent context","Twelve Data API key","MCP client supporting string search parameters"],"failure_modes":["Rate limits depend on Twelve Data subscription tier; free tier has restricted quote frequency","Latency adds ~100-500ms per request depending on Twelve Data backend load","Real-time streaming requires active MCP connection; no built-in reconnection or fallback logic","No local caching layer — every agent query hits the Twelve Data API directly","Historical data depth varies by subscription tier; free tier limited to ~1 year of data","Intraday data (1-5 minute intervals) only available for recent periods (typically last 30-90 days)","Large date ranges (e.g., 10 years of daily data) may return paginated responses requiring iteration","No built-in aggregation — requesting 1-minute data for 1 year will return ~250k+ candles, potentially exceeding context window limits","Search results limited to Twelve Data's supported instruments; some regional or delisted symbols may not be available","Fuzzy matching quality depends on Twelve Data's backend implementation; exact matches are more reliable than partial searches","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.41,"ecosystem":0.39999999999999997,"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":"2026-06-17T09:51:04.050Z","last_scraped_at":"2026-05-03T14:00:15.503Z","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=twelve-data","compare_url":"https://unfragile.ai/compare?artifact=twelve-data"}},"signature":"iIG+zDq5XlQesJYjIE9tbxH7ddwqDujhKlGda2TLH7Vv2VexZUqvIz885WzpxmPKc8fznfAAN7afNQNfcgNlDg==","signedAt":"2026-06-22T19:26:12.882Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/twelve-data","artifact":"https://unfragile.ai/twelve-data","verify":"https://unfragile.ai/api/v1/verify?slug=twelve-data","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"}}