"Overview and Applications of Mixture of Experts in Machine Learning" matching MCP servers:

Educational MCP server with 17 tools for mathematical calculations, matrix operations, statistical analysis, and data visualization. Includes persistent workspace, cloud hosting, and safety features like restricted eval.

Enables ChatGPT Web to securely control a trusted local computer through an OpenAI Secure MCP Tunnel, letting it perform file, process, Git, and other system operations on Windows, macOS, and Linux.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.

Enables AI assistants to search live jobs, view full details, save and track applications in a Kanban board, set follow-up reminders, and subscribe to job alerts—no account needed for searching.

An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.

Local design engine for AI Agents. Create, edit and export real, editable designs — social posts, flyers, print-ready PDFs — with your brand applied. Every design opens in a built-in editor, so you can click the text and fix it yourself instead of re-prompting. Bring in what you already have: InDesign, PSD, PPX and PDF files come in as editable designs. Runs on your machine, no account needed.

Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.

An MCP server that enables AI assistants to perform web searches on Perplexity.ai using browser automation instead of an official API. It supports persistent authenticated sessions and returns search results along with cited sources directly to the client.

An MCP server that demonstrates the Model Context Protocol using a mock SQLite database of an online store, offering tools for product search, sales analysis, and reviews, along with resources and prompts for learning MCP integration.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Enables natural language control of live ArcGIS Pro sessions through the Model Context Protocol, allowing inspection of projects, layers, and attributes, and execution of geoprocessing tasks.

A Model Context Protocol server that allows AI assistants and applications to access IQ.wiki data, enabling retrieval of specific wikis, user-created wikis, user-edited wikis, and detailed wiki activities.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

Integrates with Rotki portfolio tracker to provide portfolio overview, prices, transaction history, and analytics through intuitive tools for AI assistants.

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.