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Enables designing and rendering urban street cross-sections from natural language descriptions, and importing real streets from OpenStreetMap.

A production-ready MCP server built with Python, exposing 17 tools to manage users, products, and orders via a JSON-backed REST API, ready for Claude Desktop and any MCP client.

A Docker-based MCP server that provides current weather information for cities worldwide. Enables AI assistants like Claude to fetch temperature, weather conditions, and humidity data through a standardized interface.

Enables interaction with Trello boards, lists, and cards via MCP clients like Claude, allowing read, create, update, and search operations through natural language.

OpenTopography global DEM rasters + point queries (free key)

MCP server integrating VolcEngine's image generation capabilities, enabling text-to-image, image-to-image, and image set generation for AI applications.

This MCP server, developed by kazuph, uses yt-dlp to download subtitles from YouTube videos and connects them to claude.ai via the Model Context Protocol. It supports multiple languages and allows for flexible subtitle retrieval based on user-specified language codes. The implementation is designed for easy integration into Node.js projects and can be run using npx. It's particularly useful for developers looking to incorporate YouTube content analysis or transcription capabilities into their AI-powered applications, enabling natural language queries about video content through Claude.

stdio server to read markdown with images or index markdown headings from a file, folder or URL

Enables querying and verifying signed receipts of static inspections of public agent skills via read-only tools such as search_receipts, get_receipt, and get_verification_material.

A Model Context Protocol server implementation that allows AI models to interact with and manage Spinnaker deployments, pipelines, and applications through a standardized interface.

ArtifactHub MCP Server provides a bridge to Artifact Hub's Helm chart repository, enabling AI assistants to interact with Helm charts through five specialized tools. It allows retrieving chart information, accessing default values.yaml files with fuzzy search capabilities, and exploring chart templates with context-aware searching. Built with TypeScript and packaged as a Docker container, this implementation makes it particularly valuable for Kubernetes administrators and developers who need to quickly reference, search, or analyze Helm chart configurations without leaving their AI assistant conversation.

Translates wine tasting vocabulary (varietal, terroir, balance, aging) into visual parameters for AI image generation, enabling sommeliers to describe wines in their native sensory language and get corresponding visual attributes for creating wine-inspired imagery.

Enables AI agents to interact with Discord by sending notifications, creating channels, and managing interactive questions with support for two-way responses. It allows for streamlined communication through channel keys and supports various question types like multiple-choice and extended-answer modals.

A Model Context Protocol server for PyLabRobot that exposes liquid handler, plate reader, thermocycler, and heater-shaker as MCP tools. It ships in simulation mode by default, allowing end-to-end testing without hardware.

Enables clinical question answering via OpenEvidence with citation verification, including tools to ask questions, retrieve results, and follow up, plus an integrated skill to check citations against primary sources.

Enables AI assistants to search, download, and analyze Google images via SerpAPI.

Provides comprehensive IP and domain security intelligence, enabling analysis of IP addresses and domains for threat and reputation information.

Proof of concept MCP server that uses ArcGIS REST API to find places such as restaurants near a given address.

This MCP server implementation provides a bridge to various data processing and API services. It integrates with libraries like Effect, Zod, and CSV for data handling, as well as external services such as YAML parsing and date manipulation. The server is designed to facilitate complex data operations and API interactions, making it suitable for tasks involving data transformation, validation, and integration with multiple data sources and formats.