Discover our curated collection of MCP servers for data science & ml. Browse 7565 servers and find the perfect MCPs for your needs.
Enables Google News searches with automatic categorization and multi-language support via SerpAPI within Model Context Protocol environments.
Enables LLMs to search and retrieve academic paper information from Semantic Scholar and Crossref.
Enables chatting with Chronulus AI forecasting and prediction agents within Claude.
Provides an agentic abstraction layer for building high precision vertical AI agents in Python.
Provides cryptocurrency technical analysis indicators and strategies for AI trading agents.
Enables AI agent interaction with the Freqtrade cryptocurrency trading bot via its REST API for automated trading operation.
Enhances Claude 3.5 Sonnet's responses by incorporating structured reasoning from DeepSeek R1 through the OpenRouter API.
Fetches stock data, news, and financial information from Yahoo Finance using an MCP server.
Enables LLMs to accurately interpret mathematical expressions in scientific papers by fetching and processing LaTeX source from arXiv.
Augments AI models with tools, resources, and prompts using Clojure.
Bridges the LightRAG API with MCP-compatible clients, enabling Retrieval-Augmented Generation (RAG) capabilities in AI tools.
Provides a secure, unified memory layer that enables AI applications to retain context and preferences across multiple platforms.
Enables AI agents to explore Rust crate documentation, analyze source code, and confidently build Rust projects.
Empowers large language models with real-world visual perception through image object detection, localization, and captioning APIs.
Indexes codebases locally as an MCP service, enabling semantic search and integration with AI development tools like Claude Code and Gemini CLI.
Enables hybrid search and AI-powered Q&A by building knowledge graphs from diverse content sources using a configurable architecture.
Empowers AI agents with instant, up-to-date access to official Apple developer documentation and video content via a RAG system.
Serves as a powerful AI agent and IoT platform core, providing backend services for smart hardware and intelligent applications.
Empowers AI coding agents with full browser context to streamline debugging and regression testing workflows.
Analyzes large documents and codebases token-efficiently using symbolic reasoning and a logic engine, circumventing LLM context window limitations.
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