mcp-ephemeral-k8s

mcp-ephemeral-k8s

Enables spawning ephemeral Model Context Protocol (MCP) servers on Kubernetes using Server-Sent Events (SSE), supporting multiple runtimes.

Category
Visit Server

README

mcp-ephemeral-k8s

Release Build status codecov Commit activity License

A Python library for spawning ephemeral Model Context Protocol (MCP) servers on Kubernetes using Server-Sent Events (SSE).

Features

  • Supports multiple runtimes:
    • Node.js (via npx)
    • Python (via uvx)
  • Works with mcp-proxy for uvx or npx runtimes
  • Supports both local kubeconfig and in-cluster configuration
  • Can be run as MCP server

Usage

Running the MCP Server

uvx mcp-ephemeral-k8s

Using the Library

import asyncio
from mcp_ephemeral_k8s import KubernetesSessionManager, presets

async def main():
    async with KubernetesSessionManager() as session_manager:
        mcp_server = await session_manager.create_mcp_server(
            presets.K8S_MCP_SERVER, wait_for_ready=True, expose_port=True
        )
        print(mcp_server.sse_url)

if __name__ == "__main__":
    asyncio.run(main())
Job 'mcp-ephemeral-k8s-proxy-1762291156-x17zuayy' in unknown state, waiting...
http://mcp-ephemeral-k8s-proxy-1762291156-x17zuayy.default.svc.cluster.local:8080/sse

Installation

Prerequisites

  • Docker
  • Kind or any Kubernetes cluster with valid kubectl configuration

Option 1: Using uvx (Recommended)

uvx mcp-ephemeral-k8s

To connect to the MCP server, use the following config:

{
   "mcp-ephemeral-k8s": {
      "url": "http://localhost:8000/sse",
      "transport": "sse"
   }
}

Option 2: As a Python Package

pip install mcp-ephemeral-k8s
mcp-ephemeral-k8s

Option 3: Using Helm Chart

To install the Helm chart, run:

helm repo add mcp-ephemeral-k8s https://BobMerkus.github.io/mcp-ephemeral-k8s/
helm repo update
helm install mcp-ephemeral-k8s mcp-ephemeral-k8s/mcp-ephemeral-k8s

To upgrade the Helm chart, run:

helm upgrade -i mcp-ephemeral-k8s mcp-ephemeral-k8s/mcp-ephemeral-k8s

To install a specific version, run:

helm install mcp-ephemeral-k8s mcp-ephemeral-k8s/mcp-ephemeral-k8s --version <replace-with-version>

To uninstall the Helm chart, run:

helm uninstall mcp-ephemeral-k8s

Option 4: From Source

  1. Clone the repository

    git clone https://github.com/BobMerkus/mcp-ephemeral-k8s.git
    cd mcp-ephemeral-k8s
    
  2. Set up development environment

    make install
    
  3. Run pre-commit hooks

    make check
    
  4. Run tests

    make test
    
  5. Build Docker images

    make docker-build-local
    make docker-build-local-proxy
    
  6. Load images to cluster

    kind load docker-image ghcr.io/bobmerkus/mcp-ephemeral-k8s:latest
    kind load docker-image ghcr.io/bobmerkus/mcp-ephemeral-k8s-proxy:latest
    
  7. Install Helm chart

    helm upgrade -i mcp-ephemeral-k8s charts/mcp-ephemeral-k8s --set image.tag=latest
    
  8. Port forward the MCP server

    kubectl port-forward svc/mcp-ephemeral-k8s 8000:8000
    
  9. Visit the FastAPI server

    npx @modelcontextprotocol/inspector --sse http://localhost:8000/sse
    

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured