"A server for retrieving stock market data" matching MCP servers:

Provides 11 tools for stock research, including search, market history, financial statements, announcements, and data quality checks, with a local-first architecture using DuckDB and Parquet.

Unifies inventory data from four sources (Jikeyun, Supor factory, WeChat Excel, RPA) with timestamps, and exposes MCP tools for AI agents to query stock levels.

MCP server that syncs and queries comprehensive stock data (quotes, financials, dividends, analyst forecasts, options, news) from Yahoo Finance and Investing.com into an external MySQL database.

Provides comprehensive statistics and advanced analysis tools for the Korean stock market, offering real-time index data, sector analysis, investor trend tracking, and AI-based market pattern recognition.

Enables querying Rice Business Stock Market Data Portal using natural language through Claude Desktop, allowing users to ask about financial ratios, stocks, and companies.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Connect any AI to PostgreSQL, MySQL, or SQL Server — 24 dialect-aware tools for query, schema, optimization, and more.

Enables read-only auditing of product, lot, location, and stock-movement history in Tryton 6.x, transforming natural-language questions into structured investigations with movement states, lots, shipments, locations, and diagnostic balances.

Enables Claude or any MCP-capable assistant to explore and query a small business's sales, payments, invoices, and expenses through read-only SQL tools, while personal-data columns and write operations are refused by the database policy.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

Enables read-only access to public U.S. healthcare market-intelligence datasets, including catalogs, schemas, metadata, checksums, and artifact URLs. It supports CMOs, analysts, researchers, and AI agents in discovering and consuming governed market observations without patient-level data.

An MCP server with 66+ tools for data engineering, enabling AI assistants to interact with Kafka, databases, AWS, data pipelines, infrastructure, and more.

Enables agents to discover, inspect, and query municipal open datasets from data.seattle.gov through Socrata SODA2, with bounded reads, aggregates, and reference guidance.

Model Context Protocol (MCP) server providing access to 155 normalized Japanese public open datasets (10.16M+ records) including GEPS procurement, healthcare, land prices, and DuckDB SQL.

An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.