Discover our curated collection of MCP servers for data science & ml. Browse 10258 servers and find the perfect MCPs for your needs.
Provides Deepseek reasoning content to Model Context Protocol (MCP)-enabled AI Clients.
Enables AI models to explore, analyze, and interact with artworks and collections from the Rijksmuseum through natural language interactions.
Enables AI models to seamlessly search, list, and read files from Google Drive.
Provides access to Fantasy Premier League (FPL) data and tools through a Model Context Protocol (MCP) server.
Provides cryptocurrency news from CryptoPanic.com to AI agents via a simple API.
Connects Claude Desktop with DeepSeek's language models (R1/V3) using a Model Context Protocol (MCP) server implementation.
Provides a Python interface to the Perplexity API for querying responses and managing conversations.
Serves a knowledge base built using txtai for semantic search, knowledge graph querying, and AI-driven text processing.
Translates OpenAPI specifications into Model Context Protocol (MCP) tools for seamless AI agent API access.
Analyzes large codebases within IDEs using a Model Context Protocol server leveraging Gemini's extensive context window.
Enables AI assistants to search for book and author information from the Internet Archive's Open Library.
Connects large language models to the GeoServer REST API, enabling AI assistants to interact with geospatial data and services.
Provides a unified interface to numerical, logical, and symbolic solvers, leveraging MCP for problem-solving.
Provides comprehensive Taiwan Stock Exchange (TWSE) data, including real-time stock information, financial reports, ESG data, and trend analysis capabilities.
Facilitates interaction with Slack workspaces by acting as a Model Context Protocol server, providing a comprehensive set of communication and management tools.
Provides AI agents with memory management tools to store, recall, and connect information within a Neo4j knowledge graph.
Establishes a comprehensive, self-hosted memory server for Claude Code, leveraging Qdrant, Neo4j, and Ollama with Anthropic's Claude as the primary LLM.
Empowers AI agents with GDAL-style geospatial catalog discovery, metadata intelligence, and raster/vector processing, incorporating built-in reasoning guidance.
Offload routine coding and analysis tasks from Claude Code to local or cloud LLM servers, significantly reducing API token costs.
Unify organizational documents and answer natural language queries with AI.
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