Browse the catalog

MCP bridge for Demeter/Artemis EXAFS fitting. Enables headless fits, building Artemis projects, generating LaTeX reports, and launching the Artemis GUI.

The pre.dev MCP Server provides enterprise-grade specification generation for AI coding agents, replacing basic planning modes like Cursor Plan with production-ready architectural context. It offers two main tools: fast_spec for rapid prototyping (10 credits, 30-60 seconds) and deep_spec for detailed enterprise specifications (50 credits, 2-5 minutes), both supporting context integration from previous projects and automatic documentation scraping from external URLs. The server transforms AI agents from basic assistants into architectural partners by providing complete system designs with database schemas, API contracts, implementation roadmaps, and technology decisions, making it useful for MVP development, enterprise planning, feature additions, and technical documentation generation.

A lightweight AI agent that fetches real-time weather alerts for any U.S. state using the National Weather Service API.

A MCP Server to get familiarize to Model Context Protocol

Integrates xAI's Grok APIs into Claude Code to enable image and video generation, real-time web searches, and multi-modal image analysis. It provides a suite of tools for interacting with Grok models directly through natural language prompts during a Claude session.

Demonstrates secure banking operations with mock data, enabling an AI assistant to query accounts while identity and authorization are enforced via signed tokens outside the conversation.

MCP server for Indian stock market data. Provides 16 tools for quotes, history, fundamentals, mutual funds, indices, corporate actions, options, IPOs, and portfolio analysis.

Exposes 30 tools to manage Redmine resources (issues, projects, users, time entries, wiki pages, news, files, roles) via the REST API using stdio transport.

Pre-execution safety layer for autonomous agent wallets. Risk scoring, transaction simulation, and policy enforcement via MCP.

Provides intelligent code exploration tools optimized for Java and Spring Framework projects. Features batch file reading with automatic dependency expansion, structural outlines with annotation awareness (supporting @Transactional, @PreAuthorize, etc.), and precise location of classes, methods, and definitions. Includes layer-aware ordering that follows Controller to Service to Repository patterns to reveal business flow, plus smart dependency injection field detection for Spring applications.

Minecraft server manager using the Model Context Protocol.

MCP Server for TooHardBasket.ai

MCP server for managing Proxmox VE resources, VM/CT lifecycle, snapshots, backups, and clones via natural language.

This MCP server, developed by westsideori, provides accessibility testing capabilities for web applications. Built using Node.js and leveraging Puppeteer, it offers tools for automated accessibility checks and reporting. The implementation focuses on integrating accessibility testing into AI-assisted workflows, enabling AI models to perform and analyze accessibility audits. By connecting AI assistants with web accessibility tools, this server facilitates scenarios like automated WCAG compliance checks, accessibility issue detection, and generating remediation suggestions. It's particularly valuable for developers and organizations aiming to improve web accessibility through AI-powered testing and analysis.

Provides access to U.S. labor market data including employment statistics, Consumer Price Index inflation rates, and wage information. Users can query specific time series data or use shortcuts for common economic indicators like unemployment and industry-specific employment.

MCP server that controls WhatsApp Desktop via Chrome DevTools Protocol using the user's real session, enabling tools to list chats, read messages, search contacts, and send messages with simulated typing and rate limiting.

MCP server for Mnogolik (mnogolik.ru). Read-only mirror of the internal repo.

This Terminal Server implementation enables AI assistants to execute shell commands within a designated workspace directory. Built with Python using the FastMCP framework, it provides a simple but powerful interface through a single tool that captures both standard output and error streams from command execution. The server is configured to run in Claude Desktop environments through the provided configuration file, making it ideal for users who need to perform file operations, run scripts, or interact with command-line tools directly from their AI assistant conversations without leaving the interface.

Local-first persistent memory for AI agents. SQLite + sqlite-vec. Semantic search, graph relationships, anti-hallucination. Zero cloud dependency.

An MCP server that provides weather alerts and forecasts, system shutdown/restart, smart browser search, and screenshot capture.