Data Science & ML MCP Servers

Deep Dive Into AI

467

Provides educational resources for learning AI, machine learning, and deep learning using PyTorch and Apple's MLX frameworks.

Crawl4AI RAG

451

Empowers AI agents and coding assistants with web crawling and retrieval-augmented generation (RAG) capabilities.

Pg-Mcp

448

Exposes PostgreSQL databases to AI agents via the Model Context Protocol, offering rich schema discovery and query capabilities.

VectorCode

435

Indexes code repositories to provide context to LLMs for improved code completion and understanding.

MySQL

433

Enables LLMs to inspect MySQL database schemas and execute read-only queries.

Tavily

420

Integrates Tavily's search and data extraction capabilities with AI assistants via the Model Context Protocol.

Create Python

420

Quickly scaffolds Python projects for Model Context Protocol (MCP) servers.

Mcp Link

416

Converts APIs described by OpenAPI specifications into MCP-compatible interfaces for seamless integration with AI agents.

Model Context Protocol for Beginners

395

Provides an open-source curriculum designed to teach the concepts and fundamentals of the Model Context Protocol (MCP) through practical code examples.

Data Exploration

372

Facilitates interactive data exploration by turning complex datasets into actionable insights.

Rag

371

Combines search and Large Language Models (LLMs) to generate insights from your data using Retrieval Augmented Generation (RAG).

Just Prompt

359

Provides a unified interface to multiple Large Language Model (LLM) providers, simplifying interaction with services like OpenAI, Anthropic, and Google Gemini.

Neo4j

356

Enables natural language interaction with Neo4j databases and Aura accounts using the Model Context Protocol.

Jupyter

348

Enables interaction with Jupyter notebooks running in a local JupyterLab environment through the Model Context Protocol (MCP).

Memory Service

343

Provides semantic memory and persistent storage capabilities for Claude using ChromaDB and sentence transformers.

Claude Debugs

332

Enables any LLM to interactively debug code in any language through MCP and a VS Code Extension.

Wren Engine

332

Powers AI agents with a semantic engine for accessing business data with accuracy, context, and governance.

Eino Extensions

326

Extends the Eino framework with component implementations, callback handlers, and DevOps tools for building LLM applications.

AnnotateAI

319

Automatically annotates papers using Large Language Models (LLMs) to provide contextual information while reading.

Anthropic Tools

305

Enables tool use and function calling with Anthropic models, facilitating interaction with external resources.