Discover our curated collection of MCP servers for data science & ml. Browse 5736servers and find the perfect MCPs for your needs.
Integrates Perplexity's AI API with Large Language Models via the Model Context Protocol (MCP).
Extracts embedded data and SVG components from TypeScript/JavaScript source code into structured JSON and SVG files.
Enables AI assistants to search the web using the Perplexity API.
Enables data exploration within Claude Desktop by loading CSV files and executing JavaScript data analysis scripts.
Manages quantitative research context across sessions using a knowledge graph based server.
Provides Excel file manipulation capabilities without requiring Microsoft Excel installation.
Provides AI assistants with a secure and structured way to explore and analyze ClickHouse databases.
Analyzes images using OpenRouter vision models like Claude-3.5-sonnet and Claude-3-opus through a simple interface.
Enables Claude AI to interact with MySQL databases through an MCP server.
Provides logical reasoning capabilities through integration with the Coq proof assistant.
Tracks workouts, nutrition, and daily journal entries, providing AI-assisted analysis for personal well-being.
Enables Claude to maintain user context and manage profiles through Apache Unomi, a Customer Data Platform.
Integrates Tavily API to provide advanced search and content extraction capabilities via the Model Context Protocol.
Provides agentic search capabilities with support for vector search using Qdrant, full-text search using TiDB, or both combined within a Model Context Protocol (MCP) server.
Integrates Tencent Cloud services with AI applications for enhanced cloud-native development, infrastructure management, and AI-assisted workflows.
Manages cross-platform printers, offering status queries, configuration details, and file printing capabilities, primarily designed for AI assistant integration.
Performs gene set enrichment analysis using the Enrichr API within a Model Context Protocol server.
Empowers natural language querying and analysis of Weights & Biases data through the Model Context Protocol.
Enables natural language interaction with biological databases such as Protein Data Bank and ChEMBL.
Connects diverse data sources with Large Language Models using the Multi-Context Protocol, enabling intelligent querying and retrieval-augmented generation for an AI agent framework.
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