Discover our curated collection of MCP servers for data science & ml. Browse 8922 servers and find the perfect MCPs for your needs.
Identifies mutation-specific clinical trials from clinicaltrials.gov based on genetic mutations.
Recursively scans directories to discover files and folders within a file system.
Unifies multiple AI API providers, enabling AI assistants to intelligently select the most suitable model for tasks within a single conversation.
Provides a comprehensive server for the Model Context Protocol, integrating self-hosted LLM models via Ollama with a Supabase database for robust data persistence and retrieval.
Processes arXiv LaTeX sources to enable precise interpretation of mathematical expressions by Large Language Models.
Integrates Claude Desktop with PostgreSQL databases, allowing natural language queries for data exploration and analysis.
Exposes a comprehensive suite of scientific calculator operations as atomic tools for seamless integration with MCP applications.
Answers natural language questions about current weather and forecasts for any city globally.
Provides programmatic access to Apple Voice Memos on macOS, enabling AI assistants to interact with voice recordings.
Provides Large Language Models with secure, read-only access to local documentation for context-aware search and content extraction.
Manages extremely large contexts (10M+ tokens) for AI models using intelligent chunking, sub-queries, and free local inference via Ollama.
Extracts structured web content into formats like Markdown and JSON, and bridges browser tabs directly to AI agents via the Model Context Protocol.
Provides AI-powered pronunciation assessment, speech-to-text, and text-to-speech capabilities via Brainiall Speech AI APIs.
Serves a comprehensive, verified database of 5,775 Belgian statutes and 142,743 legal provisions for AI-native legal research and compliance directly through MCP-compatible clients.
Provides AI agents with persistent, structured memory, enabling them to recall and learn across sessions.
Analyzes Amazon product listings and categories to provide detailed competitor insights and automate product selection.
Provides Large Language Models with real-time, version-pinned documentation to prevent hallucinations and deprecation issues.
Parses source code repositories into a structural graph for AI agents, exposing queryable interfaces for lexical, referential, semantic, and dependency analysis.
Manages PDF documents with robust editing, cryptographic digital signing, and integrates a self-improving AI agent for advanced automation.
Provides robust long-term memory capabilities for AI agents by leveraging AWS S3 Vectors for semantic search and DynamoDB for metadata management.
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