Cloud Services MCP Repositories

Connects LLM applications to the Milvus vector database, enabling effective search and data management for AI workflows. Provides a standardized protocol for accessing vector data and integrating tools.

Connect to Bing Webmaster Tools for managing websites, submitting URLs, and analyzing traffic through AI interfaces. Leverage Bing's SEO tools to improve website performance and visibility.

Facilitates the development of web applications using expressive syntax and provides a suite of powerful tools and features to handle common web development tasks efficiently.

Integrates Kaltura's media management for uploading, retrieving, and managing media with standardized API interactions. Supports operations like metadata retrieval, media search, category management, and user permissions management.

Deploy a remote MCP server on Cloudflare Workers without requiring authentication, enabling seamless integration of custom tools and connectivity to various AI applications.

Manage Docker containers and images using standard Docker commands and Docker Compose operations, ensuring compatibility with both new and legacy versions. It provides functions for container lifecycle management, image management, and Docker Compose service operations.

Interface with Cloudflare's REST API through a lightweight MCP server deployed on Cloudflare Workers, enabling interactions with various Cloudflare tools.

Lightweight MCP server that facilitates interaction with the Neon REST API through a customizable interface on Cloudflare Workers.

Manage deployments, DNS records, and environment variables through the Vercel API. Automate interactions with Vercel projects directly from your development environment.

Facilitates interactions between agents and the WorkOS API, enabling functionalities like user management and organization handling.

Integrates with Amazon Bedrock's Nova Canvas model to generate high-quality images based on text descriptions. Provides advanced features for refining image composition through negative prompts and allows control over image dimensions and quality.

A drag-and-drop machine learning platform that utilizes Apache Spark for big data computation, enabling users to perform machine learning tasks without cloud services. It offers an intuitive interface for rapid setup and execution of data processing workflows.

Provides testing capabilities for applications, enabling code validation and ensuring reliability through comprehensive test coverage. Aims to streamline the development process and facilitate the delivery of high-quality software.