Ollama is an open-source project that allows you to run large language models (LLMs) locally on your own hardware, providing a way to use AI capabilities privately without sending data to external services.
Why this server?
Allows AI agents to route inference requests through the VibOps proxy to Ollama, with cost attribution and logging.
Why this server?
Allows managing local Ollama models: discover installed and loaded models, pull/remove models, load/unload from memory, check hardware fit, and offload inference (completion and embedding) to local Ollama instances.
Why this server?
Allows a local Ollama instance to power the healing LLM via an OpenAI-compatible endpoint.
Why this server?
Allows using local models served by Ollama as the backend for the MCP server tools by setting the DEEPSEEK_BASE_URL to the Ollama API endpoint.
Why this server?
Provides security and safety for AI agents using locally hosted Ollama models, with no API key required.
Why this server?
Allows local AI models running via Ollama to use Paigy for notifying users and awaiting replies through phone calls, banners, or push notifications.
Why this server?
Allows recording and monitoring of local Ollama LLM calls via a wrapped client, capturing trace data for observability.
Why this server?
Connects to a local Ollama daemon to observe and diagnose its behavior: token-by-token chat streaming with confidence coloring, prompt X-ray showing how each turn's prompt is composed and cached, GPU/VRAM usage mapping of loaded models, cache diagnostics and measured prompt-cache fixes, model comparison and benchmarking against curated suites, and per-turn metrics such as prefill/generation speed, time to first token and context truncation.
Why this server?
Provides automatic wiring of Ollama for AI models in deployed applications.
