Discover our curated collection of MCP servers for data science & ml. Browse 8922 servers and find the perfect MCPs for your needs.
Enables AI assistants to perform intelligent searches using the Baidu Wenxin API.
Interfaces with the Google Analytics Data API using a Model Context Protocol (MCP) server.
Generates text differences between two strings using Python's `difflib` in Unified diff format.
Enables long-term memory storage for LLM conversations using Redis Graph as a backend.
Enables listing and reading image files from a local directory, designed for integration with LLM agents.
Enables searching of vectorized Cursor IDE chat history using LanceDB and Ollama through an API service.
Connect your Discogs music collection to an LLM client to query, analyze, and get recommendations via natural language.
Fetches or generates YouTube video transcripts using AI, prioritizing official transcripts and falling back to local Whisper transcription.
Provides AI assistants with secure, read-only access to MoneyWiz financial data for natural language queries and financial analytics.
Reads various document formats including Word, PDF, and Excel, providing advanced capabilities for image extraction, structural analysis, and link validation.
Explores space through an AI-powered web application that combines cutting-edge artificial intelligence with real-time cosmic data.
Provides intelligent, persistent memory for AI assistants like Claude Code via a self-hosted Model Context Protocol (MCP) server.
Enables AI assistants to leverage local knowledge through semantic search over multi-format documents, supported by vector storage and OCR.
Enables AI assistants to interact with ComfyUI for generating images, video, audio, and 3D content.
Enables AI-guided learning and interactive practice for Data Structures and Algorithms on LeetCode.
Empowers AI assistants to access a comprehensive database of scientific papers by extracting raw experimental data, methods, and conclusions directly from full-text studies.
Facilitates multi-agent AI consultations for Claude Code, leveraging various LLMs to gather diverse second opinions and enhance decision-making.
Provides a searchable knowledge base for the AT Protocol ecosystem, offering semantic search across documentation, lexicons, and code examples.
Establishes a universal context and memory layer for AI agents, preventing repeat mistakes by capturing feedback, generating prevention rules, and injecting relevant historical context.
Enables AI agents to perform real quantitative financial analysis for enhanced trading strategies, including stock screening, backtesting, and factor analysis.
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