"Real-Time Stock Options Data for All NASDAQ Stocks" matching MCP servers:

Exposes LLM output validation (schema compliance and prompt-injection detection) as an MCP tool, enabling any MCP-compatible agent to apply real-time guardrails without importing the codebase.

Generates production-ready short video scripts from real-time web search data using Tavily and Gemini, exposed as MCP tools.

Provides comprehensive stock market data (A-shares, Hong Kong, US) including real-time quotes, K-lines, technical indicators, sectors, futures, and options, with built-in AI Skills and MCP Prompts for financial analysis.

An MCP server that exposes DSA's 问股 (Agent Chat / ask-stock) capability as a cross-client tool, allowing users to ask natural-language stock questions and list available strategy skills.

Enables AI agents and backend services to query financial market data and analysis across A-shares, US equities, ETFs, indices, and crypto — covering quotes and K-lines, technical indicators, fundamentals and valuation, money flow, news search, and SEC/China filings. Exposes these as MCP tools plus HTTP API routes with CSV/JSON export designed for code-execution workflows.

Enables AI agents and backend integrations to access standardized market data, technical indicators, fundamentals, news, filings, money-flow analysis, and code-export outputs across A-shares, US equities, ETFs, indices, and crypto. It exposes these capabilities through MCP tools and HTTP APIs.

Enables AI agents and backend integrations to access A-share, US equity, ETF, index, and crypto market data, technical indicators, fundamentals, money flow, filings, and news through MCP tools and standardized APIs.

Institutional-grade quantitative stock analysis and research signals for AI agents via the Model Context Protocol (MCP).

Provides 102 tools for end-to-end data science pipelines, enabling data loading, cleaning, visualization, modeling, and reporting via natural language.

Enables MCP clients to discover OpenRouter image and video models, generate and edit images, create variations, launch and monitor video jobs, and save resulting media into authorized local project directories with cost controls.

An MCP server that integrates SEC EDGAR, FRED, and Polygon.io financial data with OAuth 2.1 security and a citation-grounded 10-K extractor powered by Claude Sonnet 4.5.

A Model Context Protocol (MCP) server that coordinates AI agents to transform database tables into Wikipedia-style data dictionaries.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

Enables agents to detect and redact PII and secrets in text, HTML, and PDF documents before they reach an LLM, with reversible placeholder, mask, or hash redaction, and to list supported detectors and redaction styles.

Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.

Provides vision capabilities to Reasonix, enabling analysis of images/videos, OCR, and comparisons via OpenAI-compatible vision models.

Bridges DeepSeek (text-only) with vision models via MCP, enabling image description and compression using any OpenAI-compatible visual API.

An MCP server that enables AI agents to verify facts, check market and on-chain data, search the web, and run AI text tasks through five general-purpose tools, with pay-per-call USDC settlement on Base via x402 and no API key required.

Enables AI coding agents to discover and verify current open-source libraries and models using live GitHub activity, PyPI adoption, license checks, and hardware VRAM estimates before generating code.

Provides comprehensive data analysis utilities including statistical functions, probability distributions, and data processing tools through natural language.

A local-first MCP server that provides safe, governed read-only SQL access to SQLite and PostgreSQL, with validation, limits, task tracking, and report generation.

Enables statistical forecasting and anomaly detection over numerical time-series data using Holt linear smoothing, multi-step projections, and variance-based confidence bands.

Made-to-order data for AI agents via x402 micropayments on Base. Describe a need in plain language, get a custom quote, pay per call. No signup, no API keys. HTTP + MCP transports. 5 tools.

Enables agents to forecast numerical trends with zero-dependency Holt linear exponential smoothing, multi-step horizons, variance confidence bands, and supporting statistical anomaly detection, regression, hypothesis testing, and PCA.

Enables loading CSV text, filtering and aggregating datasets over Streamable HTTP, and optionally using Amazon Bedrock to turn query results into concise answers suitable for speech.

Enables agents to dynamically schedule thinking-token budgets, reflection passes, and temperature annealing while performing MCTS/process-reward verification, proof checking, and consensus voting through a standard-library STDIO MCP interface.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

Enables AI coding agents to triage BigQuery ML and BigQuery AI tasks, look up exact model and function syntax, and search 137 syntax cards, 14 reference guides, and 104 live-verified narratives via a zero-dependency stdio MCP interface.

Data Science AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables agents to dynamically allocate test-time compute, including entropy-driven thinking token budgets, temperature annealing, and reflection passes, while verifying reasoning via MCTS search with process reward modeling, counterfactual backtracking, formal proof checking, and majority-vote consensus. Runs as a zero-dependency Python MCP server over STDIO JSON-RPC for integration with Claude Desktop, Cursor, or custom agent runtimes.