Discover our curated collection of MCP servers for data science & ml. Browse 8922 servers and find the perfect MCPs for your needs.
Extends Claude's capabilities by providing a suite of Model Context Protocol (MCP) servers and specialized AI agents.
Facilitates collaborative task execution via specialized agents orchestrated through intelligent request routing.
Provides enhanced real-time search capabilities for open domain networks by integrating multiple data sources.
Provides structured access to Aster DEX market data, including candlesticks, order books, trades, and funding rates.
Gathers and processes premier global AI information for integration into LLM conversations.
Orchestrates multi-tool AI agents for real-time supply chain optimization, simulating Anthropic's low-latency FastMCP system with Gemini AI.
Manages the backend services and RDF data for the RDF Portal, enabling efficient knowledge graph operations.
Establishes a standardized protocol for managing model-context interactions in distributed applications.
Enables AI agents and tools to access Signal Desktop chat messages and attachments via the Model Context Protocol.
Performs professional AI-powered audio processing and stem manipulation for music production and engineering workflows.
Provides SQL access to the comprehensive ANSES Ciqual French food composition and nutritional database.
Integrates video, audio, and image processing with advanced AI and MCP protocol support for intelligent, natural language-driven media content creation.
Provides secure PostgreSQL database integration for Claude Code, offering read-only query execution, schema exploration, and performance analysis through the Model Context Protocol.
Manages and serves a dynamic collection of AI skills, making them discoverable and usable via the Model Context Protocol.
Provides AI assistants with institutional-grade quantitative finance tools, including real-time market data, paper trading, risk analysis, and portfolio optimization.
Leverage AI to analyze images from URLs and generate detailed descriptions using OpenAI's vision models.
Provides hierarchical Retrieval-Augmented Generation (RAG) over Lenny Rachitsky podcast transcripts, enabling efficient retrieval of insights and examples.
Augments AI agents with critical repository history and organizational knowledge to prevent regressions and improve code modifications.
Uncover and make understandable Finnish open data, serving as an MCP-server for AI and an open web service for people.
Enables AI agents to interpret Form.io JSON schemas into an understandable markdown format for automated data collection and workflow automation.
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