Descubre nuestra colección curada de servidores MCP para deployment & devops. Explora 1812 servidores y encuentra los MCP perfectos para tus necesidades.
Enables interaction with the 1Panel platform via the Model Context Protocol (MCP).
Manage AWS infrastructure using natural language commands through an intelligent AI-powered system.
Generates MCP tool definitions directly from OpenAPI specifications, enabling AI agents to access APIs described by standard specifications.
Enhances software development workflows with AI-powered automation for Kubernetes deployment, documentation testing, and shared prompt management.
Simulates HTTP traffic to benchmark and analyze web service performance.
Orchestrates production-ready AI systems, enabling organizations to deploy, manage, and scale AI with real Google API integrations and agent-optimized architecture.
Simplifies Kubernetes operations by providing an SDK-level abstraction of kubectl and client-go, offering easy resource management and MCP server capabilities.
Provides PostgreSQL database management capabilities, assisting with analysis, debugging, schema management, data migration, and monitoring.
Enables interaction with Kubernetes clusters through Model Control Protocol (MCP) tools.
Enables operations on AWS resources, including S3 and DynamoDB, through the Model Context Protocol.
Facilitates the development and testing of MCP servers by acting as both a server for Claude and a client for servers under test.
Enables AI agents to interact with the Terraform Registry API for provider, resource, and module information.
Connect functions across different languages and network boundaries to AI agents.
Orchestrates AI coding agents like Claude Code CLI and Gemini CLI to automate and manage complex coding tasks.
Build simple projects with logging and automatically fix issues based on logs for esp-idf build commands.
Provides fine-grained control over Model Context Protocol (MCP) clients, servers, and tools.
Enables Large Language Models to execute AWS Lambda functions as tools via Anthropic's Model Control Protocol (MCP) without code modifications.
Deploys a custom remote server to the cloud using Azure Functions for use with the Model Context Protocol.
Enables interaction with JFrog Platform APIs for repository management, build tracking, and more.
Integrate with the Datadog API to manage incidents, monitors, logs, dashboards, metrics, traces, and hosts.
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