A comprehensive platform for managing and proxying Model Context Protocol (MCP) servers, providing scalable AI service orchestration across multiple microservices.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"suse-ai-up": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
Add this badge to your README to show your security score and help users find safe servers.
A comprehensive, modular MCP (Model Context Protocol) proxy system that enables secure, scalable, and extensible AI model integrations.
No automated test available for this server. Check the GitHub README for setup instructions.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
Be the first to review
Have you used this server?
Share your experience — it helps other developers decide.
Sign in to write a review.
Others in ai-ml / devops
Persistent memory using a knowledge graph
MCP server for using the GitLab API
Privacy-first. MCP is the protocol for tool access. We're the virtualization layer for context.
An open-source AI agent that brings the power of Gemini directly into your terminal.
MCP Security Weekly
Get CVE alerts and security updates for Suse Ai Up and similar servers.
Start a conversation
Ask a question, share a tip, or report an issue.
Sign in to join the discussion.
A comprehensive, modular MCP (Model Context Protocol) proxy system that enables secure, scalable, and extensible AI model integrations.
🔄 MCP Proxy Service - Full-featured HTTP proxy for MCP servers with advanced session management, authentication, and protocol translation.
🔍 Network Discovery - Automated network scanning to discover MCP servers, detect authentication types, and assess security vulnerabilities.
📚 Server Registry - Curated registry of MCP Servers, including GitHub, SUSE MCP's, Atlassian, Gitea, and 20+ other popular services (yes you may contribute to the list!).
🔌 Plugin Management - Dynamic plugin system for extending functionality with service registration, health monitoring, and capability routing.
The system uses a main container + sidecar architecture where services run as coordinated containers within a single Kubernetes pod:
┌─────────────────────────────────────────────────────────────┐
│ SUSE AI Universal Proxy │
│ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ UNIFIED SERVICE │ │
│ │ │ │
│ │ • MCP Proxy with session management │ │
│ │ • Server registry and discovery │ │
│ │ • Plugin management and orchestration │ │
│ │ • Authentication and authorization │ │
│ │ │ │
│ │ HTTP: 8911 | HTTPS: 3911 │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────┐ │
│ │ PLUGINS │ │
│ │ (External) │ │
│ │ │ │
│ │ Variable │ │
│ │ Ports │ │
│ └─────────────┘ │
└─────────────────────────────────────────────────────────────┘
https://github.com/suse/suse-ai-up (branch: main)suse-ai-upservice.type: LoadBalancerauth.method: development (for no auth)Install using the helm chart:
helm install suse-ai-up ./charts/suse-ai-up
Get Service IP
kubectl get svc suse-ai-up-service -n suse-ai-up -o jsonpath='{.status.loadBalancer.ingress[0].ip}'
https://github.com/suse/suse-ai-up (branch: main)https://github.com/suse/suse-ai-up-ext(branch: v0.1.0)