"Stock Market Analysis and Market Sentiment Prediction Tools" matching MCP servers:

Enables AI agents to automate and navigate Naver SmartStore administration by providing screen and selector maps, Talk CS handling, three-step safety approvals, official help-document RAG, and search ad keyword tools.

A Model Context Protocol server that exposes over 200+ APIs from API.market as MCP resources, allowing large language models to discover and interact with various APIs through natural language commands.

MCP server that provides stock market research tools including real-time quotes, news search, semantic context retrieval, watchlist management, and saving research notes/reports.

Enables RAG-based querying of local stock company data using a local LLM and vector database, providing tools to ask questions, search raw chunks, and list documents.

MCP server that parses aviation accident reports (PDF/DOCX/TXT) and injects their content into extraction prompt templates for knowledge graph construction.

MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.

A multi-function Streamable HTTP MCP tool aggregation server that provides web search via Brave, Exa, and SearXNG with multi-key rotation and cross-provider fallback, and supports extensible tool families (URL fetch, code search, RAG) through a pluggable architecture.

Enables clinical question answering via OpenEvidence with citation verification, including tools to ask questions, retrieve results, and follow up, plus an integrated skill to check citations against primary sources.

Enables AI-powered ROI prediction and tracking with Monte Carlo simulations, Dutch market validation, and multi-project comparison. Supports natural language input for financial projections, risk analysis, and industry benchmarking across sectors like finance, healthcare, retail, and manufacturing.

Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

Guides problem-solving by breaking down complex problems into steps and recommending appropriate MCP tools for each stage, with confidence scores and rationales for tool suggestions.

A collection of tools that enhance MCP-based workflows with caching, retry logic, batch operations, and rate limiting capabilities.

An MCP server providing 22 pay-per-call utility tools for AI agents (scrape, validate, embed, store, moderate, notify, convert, prevent loops) without accounts or API keys, using USDC payments via the x402 protocol.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Enables AI-powered natural language stock market queries with real-time data from Yahoo Finance and CSV fallback. Uses Google Gemini to interpret queries and automatically fetch stock prices, comparisons, and market summaries.

A Python-based FastMCP server that provides financial tools for securities analysis, including market data, news, fundamental/technical analysis, and visualization capabilities that can be consumed by any MCP-aware client.

A multi-agent MCP server for comprehensive stock research and analysis using natural language queries, backed by SEC filings and real-time market data.

A MCP server to allow the LLM in Cursor to access Rust Analyzer, Crate Docs and Cargo Commands.

Extends VS Code Copilot with MCP tools for persistent semantic memory, code indexing and RAG search, sandboxed Python/shell execution, web fetch/search, dynamic tool management via a web UI, and structured multi-step reasoning.