Discover our curated collection of MCP servers for data science & ml. Browse 8944 servers and find the perfect MCPs for your needs.
Enables AI models to interact with the Trading Simulator API, allowing them to check balances, prices, and execute trades through an MCP-compatible interface.
Enables Large Language Models to interact with Kafka event streams using the Model Context Protocol.
Analyzes the Titanic dataset using a Model Context Protocol (MCP) server to enable data exploration and analysis with Claude.
Provides a cloud-ready service platform for executing AI-powered tools with Model Context Protocol (MCP) integration.
Orchestrates a multi-agent workflow for deep research and code generation using Gradio's Model Context Protocol (MCP) server.
Enables language models (LLMs) to access external data, tools, and custom systems via a .NET-based Model Context Protocol (MCP) server.
Transforms PDF documents into Markdown format utilizing a distributed multi-server architecture.
Provides a crash-safe, persistent memory for developer sessions, tracking progress, managing tasks, and maintaining context across AI development workflows.
Transforms command-line and web tools into asynchronous, concurrent Model Context Protocol (MCP) AI agents, enabling faster, multi-threaded AI workflows.
Exposes the Danmarks Statistik's Statistikbank API as programmable resources for easy integration with language models and AI applications.
Enables secure and efficient inter-process communication on Windows systems through memory-mapped files via the Model Context Protocol.
Enables lossless context restoration and session management for Large Language Models by persisting KV cache tensors.
Enables AI agents to securely query Northscore's sports data using the Model Context Protocol.
Provides AI agents direct access to over 1,500 World Bank development indicators across 200+ countries.
Access Twitter/X data, including user profiles, tweet search, follower events, and influencer tracking, through a simple-to-deploy Model Context Protocol server.
Connects large language models to clinical FHIR R4 data with robust governance, CDS Hooks, and multi-persona outputs.
Exposes PostgreSQL databases to AI assistants through a fixed set of structured operations and tools.
Enables AI assistants to classify galaxy images by morphological type and answer custom astronomy questions using the Qwen VL model.
Provides a local-first Model-Context Protocol (MCP) server for Shelby, enabling AI agents with secure, typed access to Shelby storage workflows.
Transforms HTML into a compact Semantic Object Model (SOM) for agents, offering significantly faster web page processing than traditional browsers.
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