Discover our curated collection of MCP servers for data science & ml. Browse 5736servers and find the perfect MCPs for your needs.
Offers a comprehensive collection of LangGraph implementations, tutorials, and advanced AI workflows.
Enables AI assistants to interact with IDA Pro for reverse engineering and binary analysis tasks.
Empowers AI assistants to interact with Power BI datasets using natural language.
Enables seamless interaction between GIMP and AI models for intelligent image editing workflows.
Implements a Model Context Protocol (MCP) server for Trino in Go, enabling AI assistants to interact with Trino's distributed SQL query engine.
Generates production-ready Model Context Protocol (MCP) server boilerplate from OpenAPI specifications, enabling exposure of existing APIs as powerful tools for AI agents.
Integrates the Perplexity API as a tool within an MCP (Managed Code Platform) environment.
Enables AI to perform data analysis on various database types (SQLite, MySQL, PostgreSQL, etc.) through a unified and secure connection configuration.
Provides real-time access to financial market data through the Alpha Vantage API.
Enables document organization and powerful searching using Claude's language model within the Needle ecosystem.
Integrates with the Box API to perform operations such as file search, text extraction, and AI-based querying.
Enables LLMs to search and retrieve academic paper information from Semantic Scholar and Crossref.
Enables AI assistants to interact with Metabase, providing access to data and analytical tools.
Connects molecular science tools to Claude AI for prompt-assisted molecule modeling and co-scientific interaction.
Provides specialized AI agents for investment research of public and private markets, accessible through a simple prompt interface.
Enables searching and fetching of articles from the PubMed database.
Provides a Model Context Protocol (MCP) server offering a suite of tools for interacting with Google Cloud's Vertex AI Gemini models, focusing on coding assistance and query answering.
Provides a developer-first framework for building portable, scalable, and secure AI agents with configuration-driven architecture and robust operational features.
Enables AI agents to explore Rust crate documentation, analyze source code, and confidently build Rust projects.
Enables Large Language Models to interact with Python environments, execute code, and manage files.
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