Data Science & ML MCP 서버

Literature Memory Server

Manages various types of sources and integrates them with knowledge graphs for enhanced research and learning.

Gdrive

Enables AI models to search, list, and read files from Google Drive.

Mynd

Gives AI applications a persistent memory of user data and context, processed and stored locally for enhanced personalization and data privacy.

SFTP by CData

Exposes SFTP data as a read-only Model Context Protocol (MCP) server for querying with Large Language Models (LLMs).

Core Lightning

Provides a standardized gRPC interface for Core Lightning nodes, enabling control via Large Language Models (LLMs) using the Model Context Protocol (MCP) specification.

WikiJS

Integrates WikiJS with AI assistants, enabling them to search and retrieve content from your WikiJS knowledge base.

Memory

Provides persistent knowledge graph-based memory capabilities for Large Language Models.

Web Scraper

Extracts web page content for AI and LLM agents, compatible with LangChainGo and MCP integration.

RE AI Assistant

Enables AI-powered malware research and reverse engineering activities within Binary Ninja, providing threat intelligence insights.

XrayDB

Provides a Model Context Protocol server to access X-ray properties of elements.

Markitdown

Converts over 29 file formats to clean Markdown, leveraging the Model Context Protocol for seamless integration with AI workflows.

Tuba Workflow

Exposes Tuba.ai computer vision workflows as callable tools for programmatic interaction by AI assistants, scripts, and services.

ROOT

Provides AI models with safe, high-level access to CERN ROOT files and their contents.

Droid

Provides AI-assisted programming capabilities by encapsulating the Factory.ai Droid CLI within a high-performance Rust MCP server.

Semango

Combines lexical (BM25) and semantic (vector) search to power natural language queries for diverse content.

Loki

Integrates with Grafana Loki to enable LLMs to query and analyze log data via the Model Context Protocol.

Oyemi

Facilitates semantic encoding, valence analysis, and word relationship discovery for AI agents.

Speech AI

Provides production-ready code examples for integrating Brainiall Speech AI APIs, including Pronunciation Assessment, Speech-to-Text, and Text-to-Speech.

PyNastran

Enables AI agents to interact with Nastran FEA models through pyNastran APIs.

Beads

Integrates the BEADS framework as a Model Context Protocol (MCP) server, enabling AI agents to interact with Beads CLI commands through structured tool invocations.