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Enables Large Language Model (LLM) clients to interact with Firebase services, including Authentication, Firestore, and Storage, via the Model Context Protocol (MCP).
Integrates with Azure AI Foundry to connect to existing Azure AI Agents, leveraging models and knowledge tools.
Provides a unified platform that combines centralized access control with intelligent tool discovery for MCP servers.
Provides an open-source, self-hosted AI workspace for developing and deploying intelligent, UI-rich AI agents that integrate with internal systems.
Automates browser testing and integrates with Cloudflare Workers and Browser Rendering.
Enables querying and managing Microsoft 365 tenants using natural language and AI through the Microsoft Graph API.
Enables AI assistants to interact with and manage Google Cloud Platform resources using natural language.
Extends the capabilities of MCP-enabled LLM AI applications with various servers implemented in Java using the Quarkus framework.
Securely executes Kubernetes commands from AI assistants like Claude by acting as a Model Context Protocol (MCP) server.
Enables AI assistants to execute AWS CLI commands in a secure, containerized environment using the Model Context Protocol (MCP).
Manage Proxmox hypervisors through a Model Context Protocol server, providing a clean interface for nodes, VMs, and containers.
Connect AWS FinOps capabilities to an AI assistant for cloud cost analysis, waste auditing, and budget insights using natural language.
Explore AWS EC2 Spot instance types, savings, prices, and interruption frequencies for optimal cloud resource selection.
Provides implementations for interacting with Alibaba Cloud Tablestore.
Manage AWS infrastructure using natural language commands through an intelligent AI-powered system.
Enables interaction with the 1Panel platform via the Model Context Protocol (MCP).
Provides AI assistants access to AWS CloudWatch Logs for analysis, searching, and correlation.
Enables Large Language Models to securely query and analyze BigQuery datasets through a standardized Model Context Protocol interface.
Simplifies Kubernetes operations by providing an SDK-level abstraction of kubectl and client-go, offering easy resource management and MCP server capabilities.
Enables operations on AWS resources, including S3 and DynamoDB, through the Model Context Protocol.
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