What is a DynamicEnv?
DynamicEnv is a Kubernetes Custom Resource (CRD) that encapsulates an entire dynamic environment setup, including multiple interdependent services, service-specific configurations, routing rules, and resource constraints.
@yonathan-shtekel
Basic information
Kubernetes MCP server for managing DynamicEnv custom resources with real-time updates and AI-driven integration.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-dynamic-env": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
DynamicEnv MCP Server is a high-performance Kubernetes MCP server that provides an AI-friendly API interface over DynamicEnv Custom Resources. It enables real-time tracking, intelligent debugging, and simplified cleanup for dynamic environments used in development, testing, and ephemeral workloads. Built with an async-first architecture, it integrates seamlessly with the Model Context Protocol (MCP) to empower developers and AI agents to manage K8s-based environments safely and efficiently.
Clone the repository, create a Python virtual environment, and install dependencies with uv pip install -e .. Then install MCP tools (pip install "mcp[cli]") and start the server using mcp dev server.py, mcp install server.py, or mcp run server.py. The core CLI tools are List (view DynamicEnvs with filtering), Status (inspect deployments, pods, logs), and Delete (safely remove a DynamicEnv instance).
DynamicEnv is a Kubernetes Custom Resource (CRD) that encapsulates an entire dynamic environment setup, including multiple interdependent services, service-specific configurations, routing rules, and resource constraints.
The server requires Python 3.9 or later and a Kubernetes cluster. Authentication can be done via in-cluster credentials or a local kubeconfig file.
It uses secure K8s authentication methods, supporting both in-cluster (service account) and kubeconfig-based credentials.
The core tools are `List` (view and filter DynamicEnvs), `Status` (inspect deployments, pods, and logs), and `Delete` (safely remove a DynamicEnv instance with dependency checks).
Yes, it implements the Model Context Protocol (MCP), allowing AI tools to subscribe to real-time updates, manage long-running operations with progress tracking, and work safely via validation and structured context.

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