data science & ml를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 7327개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
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.
Implements a Model Context Protocol (MCP) server that integrates with Vectorize for advanced vector retrieval and text extraction.
Provides safe, read-only access to SQLite databases for exploration and querying by Large Language Models (LLMs).
Enables AI agent interaction with the Freqtrade cryptocurrency trading bot via its REST API for automated trading operation.
Provides knowledge graph management capabilities for large language models, enabling persistent memory across conversations.
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 flexible server and web application for deploying Hugging Face Hub API and search endpoints.
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.
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.
Integrates Tendem's AI + Human Agent capabilities directly into various coding environments.
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