Discover our curated collection of MCP servers for data science & ml. Browse 9573 servers and find the perfect MCPs for your needs.
Provides an MCP server implementation to access policies via a GraphQL API, enabling contextual awareness for language models.
Provides a Model Context Protocol (MCP) server powered by the Tavily API for accessing business, news, finance, and political information.
Enables LLMs to analyze data, calculate statistics, and generate predictions from various sources.
Demonstrates Spring AI's integration with Model Context Protocol (MCP) for building Spring Boot applications with server and client functionalities.
Provides access to Ordnance Survey APIs through a standardized protocol.
Retrieves web content as Markdown and saves it to a local file.
Enables scalable mobile automation and development for AI agents and LLMs across iOS and Android devices.
Performs Cloudflare D1 database introspection using Model Context Protocol (MCP) and semantic intent patterns to facilitate AI-assisted development.
Access comprehensive protein data from UniProtKB via a typed, resilient interface designed for LLM agents and custom integrations.
Provides Model Context Protocol (MCP) servers to enable AI Large Language Models to seamlessly interact with DS Core's healthcare data and services.
Enhances user prompts through intelligent optimization middleware before execution.
Connects AI assistants to the Hevy workout app API, enabling them to manage fitness data, routines, and exercise progress.
Integrates Stata with AI assistants, enabling script execution, data analysis, and statistical tasks.
Automates Cardano blockchain operations through intelligent AI-powered voice commands and real-time speech recognition.
Aggregates real-time trending topics and hot search data from over 30 major platforms through unified RESTful and WebSocket APIs.
Integrates the Google Gemini CLI with AI assistants to enable powerful analysis of large files and codebases.
Manages and organizes local-first knowledge bases for LLM conversations, enabling cross-platform search and AI-powered insights.
Empower AI agents with seamless access to distributed data functions and resilience capabilities within a Hazelcast cluster.
Bridges AI agents like Claude Code to any local OpenAI-compatible vision model for image analysis.
Automates the entire research paper writing process for structural engineering, from literature review to submission-ready manuscript.
Scroll for more results...