Data Science & ML MCPサーバー
data science & ml向けの厳選されたMCPサーバーコレクションをご覧ください。9612個のサーバーを閲覧し、ニーズに最適なMCPを見つけましょう。
PentestThinking
Automates attack path planning and provides step-by-step reasoning for penetration testing, CTFs, and HTB challenges.
PingOne by CData
Enables Large Language Models (LLMs) to query live PingOne data and interact with it using natural language through a standardized Model Context Protocol (MCP) interface.
Claude Integration
Integrates the Model Context Protocol server with Claude Sonnet 4, an AI assistant, for enhanced file management and AI-powered assistance.
Gemini Pro
Integrates the Google Gemini Pro API with Claude Desktop, enabling advanced text and image analysis.
Browserbase
Empowers LLMs with cloud browser automation for web interaction, data extraction, and automated actions.
CoinMarketCap
Provides a standardized Model Context Protocol (MCP) interface for accessing CoinMarketCap's cryptocurrency market data, exchange information, and blockchain metrics.
Mcp Go
Implements the Model Context Protocol (MCP) for creating servers and clients in Go, ensuring compatibility with pydantic-ai frameworks.
Transform Rules
Transforms CSV or JSON data into structured JSON outputs using declarative YAML rules with powerful expression language and DTO generation.
Beans
Facilitates AI-powered interactions with Beans issue tracker workspaces through the Model Context Protocol.
MacroOracle
Provides access to US macro economic intelligence through a suite of eight specialized tools, leveraging data from FRED and ECB.
Audio Analysis
Processes audio for comprehensive analysis, including transcription, diarization, prosody, sentiment, and speech pattern detection.
ResQ
Connects AI agents to the ResQ platform's robotics, physics simulations, and disaster telemetry through a production-ready Model Context Protocol (MCP) server.
CanuckDUCK
Provides AI assistants with a validated Canadian policy causal knowledge graph for deep policy analysis.
ClawRiver
Enables AI agents to share and acquire practical knowledge, troubleshooting experiences, and best practices within a collaborative platform.
End of results