NetBox MCP server and chatbot
Ask your network questions in plain language, answered from NetBox by a self-hosted LLM.
AI & LLM infrastructure
Production infrastructure for LLMs and agents: hardened GPU nodes, model serving, retrieval and tool integrations, run with the guardrails and observability that production demands.
AI workloads are infrastructure workloads with sharper edges: expensive hardware, bursty demand and new failure modes. I treat them with the same rigour as any production system, from capacity planning to on-call runbooks.
Useful AI needs access to real data, safely. I prefer narrow, read-only tool interfaces such as MCP, explicit permissions and full audit trails over broad access.
Design Kubernetes-based AI infrastructure on hardened Linux GPU nodes with Terraform, Ansible and AWS, including GPU-aware placement and autoscaling.
MercorBuild production LLM and agent platforms using RAG, vector databases, vLLM / Ollama and MCP integrations.
MercorPublished a NetBox MCP server and chatbot that lets a self-hosted LLM answer questions about network infrastructure.
Open sourceAsk your network questions in plain language, answered from NetBox by a self-hosted LLM.
FAQ
Jad builds production LLM and agent platforms: Kubernetes on hardened Linux GPU nodes, GPU-aware scheduling and autoscaling, model serving with vLLM and Ollama, RAG pipelines with vector databases, and Model Context Protocol (MCP) integrations, with runbooks and guardrails.
A Model Context Protocol (MCP) server exposes tools and data to an LLM through a standard interface. Jad has published a NetBox MCP server and chatbot that let a self-hosted, OpenAI-compatible LLM query devices, sites, IP addresses and change history in NetBox in plain language.
Open to select consulting, contract and advisory work. Tell me what you are building and where it hurts.