Discover our curated collection of MCP servers for data science & ml. Browse 6867servers and find the perfect MCPs for your needs.
Demonstrates the integration of Pydantic AI agents with the Box MCP server for secure content access.
Solves mathematical problems using a client-server architecture.
Provides a curated list of Model Context Protocol (MCP) servers, highlighting their features and uses for AI-driven workflows based on discussions on X.
Deploys an authentication-less Model Context Protocol (MCP) server on Cloudflare Workers for remote tool access.
Integrates Google Search capabilities into a Model Context Protocol server for AI clients and applications.
Transforms unstructured documents into a searchable knowledge base, enabling AI-powered question answering.
Enables natural-language interactions with GitHub repositories by bridging GitHub data with chat-based AI completion.
Translates text and GitHub issue comments between languages using OpenAI models, automating translation workflows via GitHub Actions.
Empower AI agents to become high-performance managers by delegating precise tasks to specialized, deterministic tools.
Facilitates confidential AI computing and TEE infrastructure on the Phala Network as a production-ready Model Context Protocol server.
Facilitates cross-browser tab grouping through a secure server and an optional machine learning microservice for enhanced organization.
Empowers revenue teams with real-time ML insights for lead prioritization, churn prevention, and conversion maximization.
Enhances AI assistant responses by intercepting user queries, analyzing intent, and providing relevant context from various productivity systems.
Accesses OECD's comprehensive statistical data through its SDMX API, enabling AI assistants and chatbots to query various economic, health, education, and environmental datasets.
Manages local files and cloud backups intelligently, organizing folders, removing duplicates, and integrating with Google Drive for automated storage.
Enables natural language building design by connecting Claude Desktop to BULC fire simulation software.
Perform Retrieval Augmented Generation (RAG) on local codebases using a raw Python implementation with support for multiple AI providers.
Provides an MCP server interface to the CTFtime API, allowing AI assistants to retrieve information on CTF events, teams, and rankings.
Provides persistent memory, fast search, and intelligent file editing capabilities for Claude Code.
Provides comprehensive exercise-to-muscle mapping data for AI clients, detailing primary, secondary, and stabilizer muscle activation.
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