"Resources or information on financial analysis" matching MCP servers:

Provides financial stock analysis for U.S. public companies via SEC EDGAR APIs, offering tools to resolve companies, retrieve filings, calculate profitability metrics, compare periods, detect red flags, and get audit evidence, all without API keys.

Public MCP research for AI finance and trading agents: funding, bank risk and liquidity evidence. Companion SDK: persistent Python MCP sessions and Python/JS source-status streams. Setup: https://beepboop2025.github.io/financial-evidence-skills/distribution/ai-trading-tools.html. No data API key. Keep source dates, rights and gaps. No live quotes or execution.

A TypeScript MCP server for financial data aggregation that connects AI assistants to SEC EDGAR filings, XBRL statements, FRED economic indicators, and real-time market data.

MCP server to fetch Vietnamese corporate financial reports (balance sheet, income statement, cash flow) from cafef.vn using public API, no PDF or OCR needed.

Enables persona-configurable financial research and answers questions about 24 US-listed companies across three sectors, grounded in a SQLite database via MCP tools.

Institutional Financial Intelligence MCP Server for Claude Desktop & AI Agents. Sub-second market data, technical indicators, SEC EDGAR 10-K parsing, and local SQLite backtesting.

Enables querying stock quotes and computing portfolio risk/return metrics such as Sharpe ratio, drawdown, volatility, and correlations, as well as historical summaries and asset comparisons.

Enables MCP clients to retrieve stock market and company financial data, including quotes, overviews, ratios, historical prices, income statements, and stock comparisons, via a set of tools.

Enables querying and analyzing XBRL financial data through natural language, using an API key for authentication.

An MCP server that provides access to NS (Dutch Railways) travel information.

Enables access to South Korea's Ministry of Gender Equality and Family youth activity information through public data API, supporting regional searches, keyword filtering, and activity discovery for youth programs.

Provides access to the Reuters Business and Financial News API to retrieve articles, trending news, and market data. It enables searching and filtering financial content by date, author, category, and keywords.

Enables MCP clients such as Claude, Claude Code and Cursor to keyword-search a directory of over 1,000 hand-picked productivity tools, apps, AI tools, courses and books, filtering by category, type, pricing and result limit, and to fetch a single listing by slug, page URL or exact name and list all categories with counts. It runs read-only over stdio with no API key, dependencies or tracking, making only a plain GET of the public catalogue.

Provides professional-grade access to financial and economic data from Yahoo Finance and the Federal Reserve Economic Data (FRED). It enables users to perform comprehensive stock analysis, screen equities, and retrieve a wide range of macroeconomic indicators and historical data.

Enables AI agents to query Korean listed companies' financial statements, public disclosures, executive information, and shareholder structures in real-time using the DART API.

Enables querying parking lot information through an MCP server built with fastMCP, allowing users to retrieve parking facility data via API calls.

Provides access to European company data and financial filings from multiple sources including GLEIF (1.6M+ EU companies), ESEF XBRL filings (FR, DK, GB, LT, UA), UK Companies House (5M+ companies), and curated major index lists (DAX40, FTSE100, SIX).

Provides comprehensive access to financial filings from 7,700+ Asian companies through Japan's EDINET and South Korea's DART systems, enabling search, retrieval, and analysis of financial statements, XBRL data, and dimensional breakdowns.

Provides access to comprehensive U.S. economic data including GDP, personal income, and regional statistics via the Bureau of Economic Analysis API. It enables users to query datasets and retrieve specific economic indicators for states, counties, and industries through natural language.

Enables answering US economic questions by searching, fetching, and comparing FRED data series through a supervised multi-agent workflow with built-in safety and cost controls.