{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-financial-datasets","slug":"financial-datasets","name":"Financial Datasets","type":"mcp","url":"https://github.com/financial-datasets/mcp-server","page_url":"https://unfragile.ai/financial-datasets","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-financial-datasets__cap_0","uri":"capability://tool.use.integration.mcp.based.financial.data.tool.exposure.for.ai.agents","name":"mcp-based financial data tool exposure for ai agents","description":"Implements the Model Context Protocol (MCP) interface to expose a standardized set of financial data tools that AI assistants like Claude can invoke through structured tool calling. The server acts as a bridge between Claude's tool-calling mechanism and the Financial Datasets API, translating natural language requests into parameterized API calls and returning structured financial data. This architecture eliminates the need for direct API integration in the client application and provides Claude with a declarative tool schema for each financial endpoint.","intents":["Enable Claude to autonomously fetch financial data without manual API integration","Provide AI agents with structured access to stock market, financial statements, and crypto data","Standardize financial data tool interfaces across multiple AI assistant platforms via MCP protocol"],"best_for":["AI agent builders integrating financial data into Claude-based applications","Teams building financial analysis agents that need real-time market data","Developers migrating from REST API calls to MCP-based tool integration"],"limitations":["Requires Claude Desktop or MCP-compatible client to invoke tools — cannot be used with standard REST API clients","Tool invocation latency depends on Financial Datasets API response times (no local caching layer)","MCP protocol overhead adds ~50-100ms per tool call compared to direct REST API calls"],"requires":["Python 3.9+","Financial Datasets API key (from https://financialdatasets.ai)","Claude Desktop 0.1.0+ or MCP-compatible AI client","MCP server runtime (typically stdio-based transport)"],"input_types":["structured tool parameters (ticker symbol, date ranges, period type, limits)"],"output_types":["JSON-structured financial data (statements, prices, news articles, crypto data)"],"categories":["tool-use-integration","mcp-protocol"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-financial-datasets__cap_1","uri":"capability://data.processing.analysis.multi.period.financial.statement.retrieval.with.temporal.filtering","name":"multi-period financial statement retrieval with temporal filtering","description":"Retrieves structured financial statements (income statements, balance sheets, cash flow statements) for a given company ticker across multiple reporting periods, with configurable period type (annual/quarterly) and result limiting. The implementation queries the Financial Datasets API endpoint for each statement type and returns parsed JSON containing line items like revenue, expenses, assets, liabilities, and cash flows. Supports temporal filtering via period parameter to focus on specific fiscal years or quarters.","intents":["Analyze a company's financial health by comparing income statements across multiple years","Extract specific line items (e.g., revenue, net income) from balance sheets for ratio analysis","Retrieve cash flow statements to understand liquidity and capital allocation patterns"],"best_for":["Financial analysts building AI-powered due diligence tools","Agents performing fundamental analysis on publicly traded companies","Developers building financial comparison dashboards with historical context"],"limitations":["Limited to publicly traded companies with SEC filings — no private company data","Historical data availability depends on Financial Datasets coverage (typically 5-10 years for US equities)","Period parameter is constrained to 'annual' or 'quarterly' — no custom date range filtering within statements","Limit parameter caps results but does not guarantee chronological ordering (requires client-side sorting)"],"requires":["Valid stock ticker symbol (e.g., 'AAPL', 'MSFT')","Financial Datasets API key with financial statements endpoint access","Period parameter: 'annual' or 'quarterly'"],"input_types":["ticker (string)","period (enum: 'annual' | 'quarterly')","limit (integer, default typically 10)"],"output_types":["JSON array of statement objects with line items (revenue, net income, total assets, etc.)"],"categories":["data-processing-analysis","financial-data"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-financial-datasets__cap_2","uri":"capability://data.processing.analysis.real.time.and.historical.stock.price.retrieval.with.interval.based.aggregation","name":"real-time and historical stock price retrieval with interval-based aggregation","description":"Fetches current stock prices and historical price data for a given ticker with configurable time ranges and aggregation intervals (daily, weekly, monthly). The server queries the Financial Datasets API to retrieve OHLCV (open, high, low, close, volume) data and returns structured JSON with timestamp, price, and volume information. Supports both point-in-time queries (current price) and time-series queries (historical prices with from_date/to_date filtering).","intents":["Get the current market price of a stock to inform investment decisions","Retrieve historical price data to calculate technical indicators or perform trend analysis","Compare price movements across different time intervals (daily vs weekly aggregation)"],"best_for":["Trading agents that need real-time price data for decision-making","Financial analysis agents building technical analysis models","Portfolio tracking applications requiring historical price context"],"limitations":["Real-time prices may have 15-20 minute delays depending on Financial Datasets data source (not true real-time)","Historical data granularity limited to daily intervals — no intraday tick data available","Date range queries are bounded by Financial Datasets coverage (typically 20+ years for major US equities)","Volume data may be unavailable for certain tickers or time periods"],"requires":["Valid stock ticker symbol (e.g., 'AAPL', 'TSLA')","Financial Datasets API key with market data endpoint access","For historical queries: from_date and to_date in ISO 8601 format (YYYY-MM-DD)"],"input_types":["ticker (string)","from_date (ISO 8601 string, optional for current price)","to_date (ISO 8601 string, optional for current price)","interval (enum: 'daily' | 'weekly' | 'monthly', optional)"],"output_types":["JSON object with current price and metadata (for get_current_price)","JSON array of OHLCV candles with timestamp (for get_prices)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-financial-datasets__cap_3","uri":"capability://search.retrieval.company.news.and.market.sentiment.retrieval.with.result.limiting","name":"company news and market sentiment retrieval with result limiting","description":"Retrieves recent news articles and market sentiment data for a given company ticker from the Financial Datasets API, with configurable result limiting to control the number of articles returned. The server queries the news endpoint and returns structured JSON containing article metadata (headline, source, publish date, summary) that Claude can analyze for sentiment or relevance. Supports filtering by ticker to focus on company-specific news rather than broad market news.","intents":["Fetch recent news about a company to inform investment thesis or risk assessment","Analyze market sentiment around a stock by reviewing recent article headlines and summaries","Build a news-driven trading signal by monitoring breaking news for specific companies"],"best_for":["Sentiment analysis agents that correlate news with price movements","Investment research agents building comprehensive company profiles","News-driven trading bots that react to breaking news"],"limitations":["News data is limited to sources indexed by Financial Datasets (may not include all news outlets)","Articles are typically 1-2 days old due to indexing lag — not true real-time news","No filtering by news sentiment or source credibility — requires client-side filtering","Limit parameter is hard-capped (typically 50-100 articles) to prevent excessive API usage"],"requires":["Valid stock ticker symbol (e.g., 'AAPL', 'NVDA')","Financial Datasets API key with news endpoint access"],"input_types":["ticker (string)","limit (integer, default typically 10)"],"output_types":["JSON array of news article objects with headline, source, publish_date, summary"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-financial-datasets__cap_4","uri":"capability://data.processing.analysis.cryptocurrency.price.and.ticker.enumeration.with.multi.asset.support","name":"cryptocurrency price and ticker enumeration with multi-asset support","description":"Provides cryptocurrency market data capabilities including listing all available cryptocurrency tickers in the Financial Datasets catalog and retrieving current/historical prices for crypto assets. The server exposes three crypto-specific tools: get_available_crypto_tickers (returns list of supported tickers), get_current_crypto_price (returns current price for a ticker), and get_crypto_prices (returns historical OHLCV data with date range filtering). Crypto data is sourced from Financial Datasets and supports the same interval-based aggregation as stock prices.","intents":["Discover which cryptocurrencies are available in the Financial Datasets catalog","Monitor current prices of Bitcoin, Ethereum, and other crypto assets","Analyze historical crypto price movements to identify trends or support resistance levels"],"best_for":["Crypto trading agents that need multi-asset price data","Portfolio managers tracking both traditional and digital assets","Agents building crypto market analysis models"],"limitations":["Crypto ticker coverage is limited to assets indexed by Financial Datasets (may not include all altcoins)","Historical crypto data availability varies by asset (major assets like BTC/ETH have 10+ years; newer assets have shorter history)","Crypto prices may have higher volatility and data quality issues compared to traditional equities","No order book or liquidity data — only OHLCV candles available"],"requires":["Financial Datasets API key with cryptocurrency endpoint access","Valid cryptocurrency ticker (e.g., 'BTC', 'ETH', 'SOL')"],"input_types":["ticker (string, for price queries)","from_date (ISO 8601 string, optional)","to_date (ISO 8601 string, optional)","interval (enum: 'daily' | 'weekly' | 'monthly', optional)"],"output_types":["JSON array of ticker strings (for get_available_crypto_tickers)","JSON object with current price and metadata (for get_current_crypto_price)","JSON array of OHLCV candles (for get_crypto_prices)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-financial-datasets__cap_5","uri":"capability://safety.moderation.parameter.validation.and.error.handling.for.financial.data.queries","name":"parameter validation and error handling for financial data queries","description":"Implements server-side validation of tool parameters (ticker symbols, date ranges, period types, limits) before querying the Financial Datasets API, with structured error responses that Claude can interpret. The MCP server validates inputs against expected types and constraints (e.g., from_date must be before to_date, limit must be positive integer) and returns descriptive error messages when validation fails. This prevents malformed API calls and provides agents with clear feedback for retry logic.","intents":["Prevent invalid API calls by validating parameters before sending to Financial Datasets","Provide Claude with clear error messages to enable intelligent retry or fallback logic","Ensure data consistency by enforcing constraints (e.g., date range ordering, ticker format)"],"best_for":["Agents that need robust error handling for financial data queries","Applications requiring high reliability and minimal API failures","Developers building financial agents that must handle edge cases gracefully"],"limitations":["Validation is limited to parameter format and type — does not validate ticker existence (requires API call)","Error messages are generic and may not provide specific guidance for fixing invalid tickers","No rate limiting or quota enforcement at the MCP server level — relies on Financial Datasets API limits"],"requires":["MCP server implementation with parameter validation logic","Financial Datasets API key (for downstream validation via API calls)"],"input_types":["tool parameters (ticker, dates, limits, periods)"],"output_types":["validation error messages (JSON with error code and description)","successful query results (if validation passes)"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-financial-datasets__cap_6","uri":"capability://tool.use.integration.claude.desktop.integration.via.stdio.based.mcp.transport","name":"claude desktop integration via stdio-based mcp transport","description":"Configures the Financial Datasets MCP server to run as a stdio-based subprocess that Claude Desktop can invoke, enabling seamless tool integration without manual API management. The server implements the MCP protocol's stdio transport layer, allowing Claude Desktop to spawn the server process, send tool invocation requests via stdin, and receive responses via stdout. Configuration is managed through Claude Desktop's config file (typically ~/.claude/config.json on macOS/Linux), which specifies the server command and environment variables (API key).","intents":["Enable Claude Desktop users to access financial data tools without manual API setup","Provide a native Claude Desktop integration that feels like built-in functionality","Simplify deployment by eliminating the need for separate server infrastructure"],"best_for":["Claude Desktop users who want financial data access without technical setup","Teams deploying Claude Desktop with financial analysis capabilities","Individual developers building personal financial analysis assistants"],"limitations":["Requires Claude Desktop 0.1.0+ — not compatible with Claude web interface or API","Server runs locally on the user's machine — no cloud-based scaling or multi-user support","API key must be stored in Claude Desktop config file — requires secure key management","Stdio transport has no built-in authentication or encryption — relies on local file system security"],"requires":["Claude Desktop 0.1.0+","Python 3.9+ installed on the local machine","Financial Datasets API key","Write access to Claude Desktop config file (~/.claude/config.json or equivalent)"],"input_types":["MCP server configuration (command, environment variables)"],"output_types":["stdio-based MCP protocol messages (JSON-RPC)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-financial-datasets__cap_7","uri":"capability://planning.reasoning.agentic.financial.data.orchestration.for.multi.step.analysis","name":"agentic financial data orchestration for multi-step analysis","description":"Enables Claude to autonomously chain multiple financial data tool calls to perform complex analysis workflows (e.g., fetch income statement → calculate ratios → retrieve news → assess sentiment). The MCP server provides individual tools that Claude can invoke sequentially based on its reasoning, allowing the agent to decide which data to fetch next based on previous results. This capability leverages Claude's native tool-calling and planning abilities without requiring explicit workflow orchestration logic in the server.","intents":["Build multi-step financial analysis workflows where each step depends on previous results","Enable Claude to autonomously gather comprehensive company profiles by chaining data requests","Create investment thesis generation agents that synthesize multiple data sources"],"best_for":["Financial analysts building AI-powered due diligence workflows","Investment research teams automating company analysis","Agents performing comprehensive fundamental analysis with multiple data sources"],"limitations":["No built-in state management — Claude must track context across tool calls (limited by context window)","Tool call latency compounds across multi-step workflows (each call adds 50-200ms)","No built-in caching — repeated queries for the same data result in duplicate API calls","Claude's reasoning may not always select the optimal sequence of tool calls for complex analysis"],"requires":["Claude model with strong planning and reasoning capabilities (Claude 3.5+)","Multiple financial data tools exposed via MCP server","Sufficient context window to track multi-step analysis (8K+ tokens recommended)"],"input_types":["natural language financial analysis requests"],"output_types":["synthesized analysis combining multiple data sources (text, structured data)"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"high","permissions":["Python 3.9+","Financial Datasets API key (from https://financialdatasets.ai)","Claude Desktop 0.1.0+ or MCP-compatible AI client","MCP server runtime (typically stdio-based transport)","Valid stock ticker symbol (e.g., 'AAPL', 'MSFT')","Financial Datasets API key with financial statements endpoint access","Period parameter: 'annual' or 'quarterly'","Valid stock ticker symbol (e.g., 'AAPL', 'TSLA')","Financial Datasets API key with market data endpoint access","For historical queries: from_date and to_date in ISO 8601 format (YYYY-MM-DD)"],"failure_modes":["Requires Claude Desktop or MCP-compatible client to invoke tools — cannot be used with standard REST API clients","Tool invocation latency depends on Financial Datasets API response times (no local caching layer)","MCP protocol overhead adds ~50-100ms per tool call compared to direct REST API calls","Limited to publicly traded companies with SEC filings — no private company data","Historical data availability depends on Financial Datasets coverage (typically 5-10 years for US equities)","Period parameter is constrained to 'annual' or 'quarterly' — no custom date range filtering within statements","Limit parameter caps results but does not guarantee chronological ordering (requires client-side sorting)","Real-time prices may have 15-20 minute delays depending on Financial Datasets data source (not true real-time)","Historical data granularity limited to daily intervals — no intraday tick data available","Date range queries are bounded by Financial Datasets coverage (typically 20+ years for major US equities)","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.26,"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":"2026-06-17T09:51:03.039Z","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=financial-datasets","compare_url":"https://unfragile.ai/compare?artifact=financial-datasets"}},"signature":"iysCxilY3EJvFpbSFmjW3GZ+W9Zj2sclZrsvhKRcftWDsxJertznGab6HhtKgLLqsSxwl9qdaWqFc20HN8PmDg==","signedAt":"2026-06-20T01:06:16.560Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/financial-datasets","artifact":"https://unfragile.ai/financial-datasets","verify":"https://unfragile.ai/api/v1/verify?slug=financial-datasets","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"}}