Cloud Services MCP Repositories

Integrate Large Language Models with various tools and data sources using the Model Context Protocol for secure and efficient data access. Supports implementations in both Typescript and Python to enhance LLM capabilities and streamline workflows.

Run Kubernetes commands using a specified kubeconfig path and provide interpretations of those commands. This server supports custom kubeconfig paths, automatic kubectl installation checks, and includes error handling features.

Provides secure, read-only access to Snowflake databases for streamlined data retrieval processes, ideal for analytics and reporting without modifying data.

Dify allows users to build and test AI workflows on a visual canvas, facilitating the integration of tools and data sources for enhanced AI interactions. It supports both cloud hosting and self-hosting options for flexible usage.

A collection of DSL workflow scripts for the Dify platform, enabling users to import and utilize various scripts to enhance their Dify experience for personal use and learning.

Facilitates in-depth investment research by integrating with the Octagon Market Intelligence API, enabling detailed analysis of SEC filings, earnings calls, financial metrics, and real-time stock market data.

The Sui Tools MCP server allows users to interact with the Sui blockchain easily. It offers tools for checking balances, transferring assets, and managing SUI transactions without complex setups.

Send and manage emails using multiple SMTP configurations, create and utilize reusable email templates, and perform bulk email sending with comprehensive logging and dynamic content support.

Standardized interface for interacting with Azure Data Lake Storage Gen2, facilitating file operations through MCP tools.

Integrates existing Azure AI Agents with MCP clients for streamlined workflows, providing secure access to conversation histories and interactions. Leverages Azure AI Foundry's advanced models and tools for varied use cases.

Provides advanced reasoning capabilities utilizing distilled models for enhanced performance in mathematical, coding, and reasoning tasks. Designed to assist in a variety of applications requiring sophisticated model interactions.

This server provides a connection to the Dameng 8 database using the Model Context Protocol (MCP), allowing users to easily access and integrate database content for more efficient data utilization.

Establish a distributed endpoint for interacting with Large Language Models, leveraging OAuth 2.0 for robust access control. This service is designed for deployment atop Cloudflare Workers, offering a streamlined API interface for diverse client applications.

The Safe MCP Server allows users to interact with Safe smart contract wallets, enabling them to query transaction histories, access multisig details, and decode transaction data easily through an integration with the Safe API.

Facilitates integration with Smartsheet for automated document operations and enhances healthcare analytics through AI-driven insights. Supports intelligent document management and analysis aligned with compliance and data integrity standards.

Enhances LLM capabilities by creating and searching knowledge graphs, allowing for improved data structuring and retrieval.

A Python implementation facilitating interaction with Microsoft SQL Server databases via the standardized Model Context Protocol (MCP) interface, supporting schema introspection and arbitrary SQL command execution.

Manage local MCP Servers and authorize specific tools across MCP clients. Provides a lightweight service for configuring and maintaining MCP server settings.

Showcases reference implementations for the Model Context Protocol (MCP), providing secure and controlled access to tools and data sources for Large Language Models (LLMs). Implemented with either the Typescript or Python MCP SDK, these servers demonstrate the versatility and extensibility of MCP.

A standardized Model Context Protocol (MCP) server providing comprehensive programmatic access to core Azure DevOps features, including item management, source control operations, pipeline visibility, and project lifecycle administration. This utility streamlines development lifecycle automation.

Run LLM prompts and interact with MCP-compatible servers directly from the terminal, enabling access to various LLM providers and execution of commands with AI assistance.

Connects AI assistants to Portkey's API for managing AI configurations, workspaces, analytics, and user access.

Facilitates the connection of Ollama's locally-hosted generative AI models with the Model Context Protocol (MCP) framework. This component ensures secure, private execution of local language models via a standardized interface for resource administration and task execution.

An interface for seamless editing and deployment of web projects, with integration options for IDEs and direct editing in GitHub. It supports custom domains, instant previews, and automatic synchronization of project changes.

Manage Coolify instances by overseeing teams, servers, and services. Facilitate application lifecycle actions, deployment tracking, and private key management while also monitoring version and health status.

Provides real-time weather forecasts for various cities and regions, enabling queries for local weather conditions based on city or region names. It retrieves accurate weather data for application enhancement.

A sophisticated server application interfacing with the PiAPI gateway, engineered to orchestrate the creation of diverse multimedia assets utilizing advanced generative models such as Midjourney, Flux, Kling, and others. This component ensures seamless integration of AI capabilities within any application supporting the Model Context Protocol (MCP) framework for on-demand content production.

Provides text-to-speech, voice cloning, and multimedia generation capabilities through a unified interface. It integrates with MCP clients to facilitate the generation of speech and multimedia content seamlessly.

Interacts with Kayzen advertising campaign data through a standardized interface, facilitating data analysis and report management. It includes automated authentication, comprehensive error handling, and supports TypeScript with environment-based configuration.

Interact with Jupyter notebooks in a local JupyterLab environment, enabling the addition and execution of code or markdown cells.