Offload coding/text tasks to a local LLM (Ollama) to save Claude API tokens. Use for code generation, refactoring, formatting, boilerplate, and other routine tasks.

Compress/summarize large text content using a local LLM to reduce cloud token usage. Use for summarizing logs, large files, or verbose context before sending to Claude.

View cumulative cost savings and model usage statistics.

Submit multiple coding tasks as a batch to the local LLM. Tasks are processed sequentially or in parallel. Supports partial failure.

Get server metrics in Prometheus text format or JSON. Includes request counts, latency, queue stats, cost savings, and health status.

Recommend the best local LLM model for a given task category based on system specs and installed models. Returns prioritized list with installation status and license info.

Preload a model into VRAM for warm inference. Sends an empty chat request with keep_alive to keep the model loaded during the session.

List all models currently loaded in VRAM with usage details. Shows VRAM usage, expiry time, and available slots.

Download a model from the Ollama registry to local storage. Use this to install recommended models before preloading them into VRAM.

View or modify model selector settings at runtime. Manage blocked models, license filters, and custom model recommendations.

Automate the full model setup flow: recommend the best model for a task category, download it if needed, and preload it into VRAM — all in one step.