Description
Provide an MCP Server implementation for customers to access data on scc.suse.com via MCP protocol. The core benefit of this MCP interface is that it has direct (read) access to customer data in SCC, so the AI agent gets enhanced knowledge about individual customer data, like subscriptions, orders and registered systems.
Architecture
Goals
We want to demonstrate a proof of concept to connect to the SCC MCP server with any AI agent, for example gemini-cli or codex. Enabling the user to ask questions regarding their SCC inventory.
For this Hackweek, we target that users get proper responses to these example questions:
- Which of my currently active systems are running products that are out of support?
- Do I have ready to use registration codes for SLES?
- What are the latest 5 released patches for SLES 15 SP6? Output as a list with release date, patch name, affected package names and fixed CVEs.
- Which versions of kernel-default are available on SLES 15 SP6?
Technical Notes
Similar to the organization APIs, this can expose to customers data about their subscriptions, orders, systems and products. Authentication should be done by organization credentials, similar to what needs to be provided to RMT/MLM. Customers can connect to the SCC MCP server from their own MCP-compatible client and Large Language Model (LLM), so no third party is involved.
Milestones
[x] Basic MCP API setup MCP endpoints [x] Products / Repositories [x] Subscriptions / Orders [x] Systems [x] Packages [x] Document usage with Gemini CLI, Codex
Resources
Gemini CLI setup:
~/.gemini/settings.json:
{
"mcpServers": {
"SCC local http": {
"httpUrl": "http://localhost:3000/mcp",
"note": "MCP server for SUSE Customer Center"
}
}
}
Results
After 5 days of hackweek, we have good results for the 4 example questions from above:
This project is part of:
Hack Week 25
Activity
Comments
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Resources
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- https://modelcontextprotocol.io/docs/develop/build-server
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Example execution
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Self-Scaling LLM Infrastructure Powered by Rancher
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Project Charter
Description
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Description
The idea is to implement the SUSE Observability Model Context Protocol (MCP) Server as a specialized, middle-tier API designed to translate the complex, high-cardinality observability data from StackState (topology, metrics, and events) into highly structured, contextually rich, and LLM-ready snippets.
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- MCP Server v0.1 A running Golang MCP server with at least one tool.
- A README.md and a test script (e.g., curl commands or a simple notebook) showing how an AI agent would call the endpoint and the resulting JSON payload.
Outcome A functional and testable API endpoint that proves the core concept: translating complex StackState data into a simple, LLM-ready format. This provides the foundation for developing AI-driven diagnostics and automated remediation.
Resources
- https://www.honeycomb.io/blog/its-the-end-of-observability-as-we-know-it-and-i-feel-fine
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- https://modelcontextprotocol.io/specification/2025-06-18/index
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Results
Successfully developed and delivered a fully functional SUSE Observability MCP Server that bridges language models with SUSE Observability's operational data. This project demonstrates how AI agents can perform intelligent troubleshooting and root cause analysis using structured access to real-time infrastructure data.
Example execution
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Description
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Resources
Result
https://github.com/e-minguez/eib-mcp
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* hostname: node2, IP: 1.1.1.2, role: agent
* hostname: node3, IP: 1.1.1.3, role: agent
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called "suse" with password "suse" and set ntp to "foo.ntp.org". The VIP address for the API should be 1.2.3.4
Generates:
``` apiVersion: "1.0" image: arch: x86_64 baseImage: slmicro-6.2.iso imageType: iso outputImageName: my-edge-image kubernetes: helm: charts: - name: cert-manager repositoryName: jetstack
Review SCC team internal development processes by calmeidadeoliveira
Description
Continue with the Hackweek 2024, with focus on reviewing existing processes / ways of working and creating workflows:
Goals
- Check all the processes from [1] and [3]
- move them to confluence [4], make comments, corrections, etc.
- present the result to the SCC team and ask for reviews
Resources
[1] https://github.com/SUSE/scc-docs/blob/master/team/workflow/kanban-process.md [2] https://github.com/SUSE/scc-docs/tree/master/team [3] https://github.com/SUSE/scc-docs/tree/master/team/workflow
Confluence
[4] https://confluence.suse.com/spaces/scc/pages/1537703975/Processes+and+ways+of+working