Discover our curated collection of MCP servers for data science & ml. Browse 6536servers and find the perfect MCPs for your needs.
Access anime, manga, and user data from AniList via the Model Context Protocol.
Enables AI models to seamlessly search, list, and read files from Google Drive.
Provides cryptocurrency news from CryptoPanic.com to AI agents via a simple API.
Translates OpenAPI specifications into Model Context Protocol (MCP) tools for seamless AI agent API access.
Connects language models to web3 tools through the Heurist Mesh network.
Connects AI applications to Airtable for seamless data access and management via Anthropic's Model Context Protocol (MCP).
Fetch and analyze web analytics data from Google Analytics 4 using Large Language Models.
Provides a Metadata Change Proposal (MCP) server implementation for data governance.
Conducts iterative, deep research using search engines, web scraping, and Gemini LLMs to create an AI Research Agent.
Analyzes large codebases within IDEs using a Model Context Protocol server leveraging Gemini's extensive context window.
Enables natural language control of a Unitree Go2 robot via a Model Context Protocol (MCP) server.
Automates optimization and analysis using Optuna APIs through the Model Context Protocol.
Enables AI assistants to perform advanced PDF processing operations by integrating with the Nutrient Document Web Service (DWS) Processor API.
Enables control of SO-ARM100 series robots via an MCP server for AI agents and direct manual operation.
Empowers AI assistants with programmatic access to Linux kernel tracing capabilities using bpftrace.
Facilitates access to Turkish government tender information via a Model Context Protocol (MCP) server for LLM applications and other clients.
Provides a lightweight and secure Python code execution sandbox based on IPython and Docker, designed for AI agents.
Automatically generate read-only APIs for datasets using SQL templates, leveraging DuckDB for performant and cost-efficient data exposure.
Connects AI agents and tools with ROS 2 nodes, topics, and services via the Model Context Protocol (MCP) over stdio.
Provides an infrastructure layer for AI agents to connect and manage tools across various environments.
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