Data Science & ML MCP 服务器

发现我们为 data science & ml 精心策划的 MCP 服务器集合。浏览 3288 个服务器，找到满足您需求的完美 MCP。

Provides intelligent summarization capabilities for various content types using Google's Gemini 1.5 Pro model.

Curates a list of Model Context Protocol (MCP) servers specifically for cryptocurrency-related applications.

Exposes your Zotero library to AI assistants via the Model Context Protocol.

Index, search, and analyze code repositories with large language models using a Model Context Protocol server.

Enables Language Models (LLMs) to seamlessly connect to and retrieve data from various databases through a unified API.

Integrates MiniZinc constraint programming with Large Language Models via the Model Context Protocol for constraint optimization and solving.

Enables AI assistants to interact with HubSpot CRM data, leveraging vector storage and caching for improved performance.

Empowers local developers with efficient internet search and content retrieval for Large Language Models, saving tokens.

Builds AI agents that interact with the Starknet blockchain using multiple AI providers.

Provides knowledge graph management capabilities for large language models, enabling persistent memory across conversations.

Provides examples and tutorials for building AI applications using the watsonx.ai Flows Engine.

Showcases a .NET eCommerce application with semantic search, managed context protocol (MCP), and reasoning models.

Integrates Google's Gemini AI capabilities into Claude Code, providing a powerful AI assistant with a massive context window for code analysis.

Deploy Haystack pipelines as REST APIs and MCP Tools with ease.

Enhance Livebook development with AI code editing, model context protocol servers, and command-line execution of Livebooks.

Bridges AI assistants with StarRocks databases, enabling direct SQL execution and database exploration.

Enables LLMs to perform precise numerical calculations via a Model Context Protocol server.

Executes and debugs AI agent workflows with Dockerized tools directly within VS Code.

Enables AI models to interact with MySQL databases through a standardized interface.

Enables seamless integration between Ollama's local LLM models and Model Context Protocol (MCP) compatible applications.

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