local-llm-router

Route coding queries to local LLMs in an air-gapped environment by detecting available local model services and forwarding requests to the most suitable endpoint. This ensures secure, private model routing without leaving the offline network boundary.

Yes, Serena MCP integrates with offline local LLMs to provide semantic code understanding. It improves symbol-level awareness and enables precise code changes by applying context from local models like Ollama, LM Studio, and Jan.

You can use Ollama, LM Studio, Jan, or OpenWebUI as local LLM services for offline AI coding assistance. The routing mechanism detects available models across these platforms and forwards queries to the best matching endpoint.

Before routing queries to local models, you must install Serena MCP and ensure at least one local LLM service is running. You also need to verify endpoint health, model, and chat APIs to establish a deterministic quick-start workflow.

Use local LLM routing instead of cloud-based models to maintain strict air-gapped security and data privacy. It enables secure, offline development workflows by leveraging local agents and semantic code understanding without transmitting data externally.