"Setting Up MCP (Minecraft Control Panel or Related Tool) Helper" matching MCP servers:

MCP server for Kaggle API integration that allows creating, running, and managing Kaggle notebooks programmatically.

A read-only MCP server for searching control science and engineering papers via OpenAlex, limited to core journals in the field.

Query public BeatLeader profiles and scores from MCP clients to review performance, choose practice maps, and compare later results.

Enables searching, ingesting, and querying academic papers using natural language, with integration to arXiv and Semantic Scholar.

Enables searching and retrieving articles, citations, and structured content from Grokipedia for research and information retrieval. It provides specialized tools for section extraction, related page discovery, and filtered search results.

Enables AI agents to operate DSpace repositories through a typed interface, including SAF package building, metadata editing, scientometric harvesting, open-access PDF downloads, and repository administration.

A Node.js-based MCP server that extracts numbers from text and generates statistical chart data such as bar, pie, and line charts based on frequency. It enables AI agents to perform data extraction and visualization tasks through the Model Context Protocol.

Enables researchers to present 12 mock file, memory, schedule, and database tools over stdio and collect LLM pre-execution judgments (EXECUTE/CONFIRM/REFUSE) without executing real operations.

Enables discovery and analysis of research ecosystems by extracting metadata from paper URLs, GitHub repositories, and research names. Automatically finds related papers, code repositories, models, datasets, and authors across platforms like arXiv, HuggingFace, and GitHub.

Provides accurate competitive Pokémon information for Pokémon Champions, including damage calculation, type effectiveness, Pokémon data, and regulation legality checks.

Enables AI assistants to run live Semrush SEO analysis—keyword research, domain analytics, backlink analysis, competitor intelligence, and traffic insights—through natural language MCP tools.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

Remote MCP server for AI-powered competitor intelligence, enabling real-time analysis of any product URL through tools like analyze_competitor and report retrieval.

Provides AI assistants with access to real-time space weather data and forecasts from NOAA's Space Weather Prediction Center, enabling queries and interpretations of geomagnetic storms, solar flares, and related indices.

Enables AI agents to interact with Jupyter notebooks via MCP tools for querying, modifying, executing, and setting up notebooks, with state preservation and real-time collaboration.

Enables AI clients to analyze any company domain and determine its AI maturity tier (commercialized, deployed, declared, or none) with supporting evidence, via a single tool backed by an Apify actor.

Enables querying Google Trends data directly from conversational MCP clients, including search interest over time, related queries and topics, regional breakdowns, and trending searches, for market research without leaving the chat.

Enables classical test theory analysis, differential item functioning, local item dependence detection, and standard setting through MCP tools.

Read any public web page as a clean AIDocument: Markdown plus title, description, and structure, with navigation and boilerplate stripped. Reads resolve through Lyrenth's shared cache, so it is far fewer tokens than raw HTML and origin-friendly.

Pull open jobs from Workday, Greenhouse, Lever and Ashby career sites as normalized JSON with one tool call. Change tracking returns only jobs added, edited or closed since the previous run. Calls the hosted Apify Actor: set APIFY_TOKEN; tool calls are billed pay-per-event on Apify. No browser, login or proxy.