Discover our curated collection of MCP servers for data science & ml. Browse 6536servers and find the perfect MCPs for your needs.
Provides real-time hot trending topics from major Chinese social platforms and news sites via the Model Context Protocol.
Provides a Model Context Protocol (MCP) implementation for the Opik platform, enabling seamless IDE integration and unified access to LLM application data.
Provides a local Model Context Protocol (MCP) server for interacting with MongoDB databases using natural language queries.
Retrieves information from Wikipedia to provide context to Large Language Models (LLMs).
Simplifies the creation of Model Context Protocol (MCP) servers in TypeScript.
Connects AI models to SEC EDGAR filings through an open-source MCP server, enabling financial research and insights.
Provides comprehensive financial data from Yahoo Finance via the Model Context Protocol.
Enables Java and Spring applications to interact with AI models and tools through the Model Context Protocol.
Provides access to Polygon.io financial market data via a Model Context Protocol (MCP) server, enabling LLMs to retrieve real-time and historical market information.
Enables AI assistants and LLM applications to securely execute code snippets within isolated containerized environments.
Dynamically generate visual charts and diagrams using Apache ECharts with AI-powered capabilities for data analysis.
Provides an open-source, self-hosted AI workspace for developing and deploying intelligent, UI-rich AI agents that integrate with internal systems.
Integrate Universal Tool Calling Protocol (UTCP) capabilities directly into the Model Context Protocol (MCP) ecosystem through a versatile, all-in-one server.
Provides persistent, searchable local memory for AI assistants, LLMs, and Copilot within VS Code.
Orchestrates experimental, small-scale engineering agents with multi-provider LLM support for comparative evaluation.
Provides an MCP server to enable AI-powered video generation and remixing through OpenAI's Sora 2 API.
Facilitates true deliberative consensus among AI models by enabling multi-round debates to refine positions and reach informed decisions.
Empowers AI assistants to securely execute code in blazing-fast, isolated cloud containers across multiple programming languages.
Enables LLMs to interact with applications and navigate complex service hierarchies through a declarative Agentic AI framework.
Captures an engineering playbook to provide AI context, guardrails, and governance for coding agents.
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