add-ollama-tool

Integrate local Ollama models into a containerized agent by registering an MCP server within the agent configuration. This connects the agent to a running Ollama daemon on the host, enabling private, low-latency inference tasks.

Yes, you can use an MCP server to manage your Ollama library. The integration optionally allows the agent to pull new models, delete unused ones, and inspect existing models directly from the Ollama registry.

Yes, a running Ollama daemon on the host machine is required for local model inference. The containerized agent environment communicates with this daemon via an explicitly registered MCP server to perform text generation.

Offload text processing to local Ollama models to ensure private data stays on your machine while maintaining agent-driven orchestration. This approach provides secure, isolated, low-latency AI inference without relying solely on cloud models.

The best way to expose Ollama model discovery is through an MCP server integration. This setup supports model discovery and text generation, allowing the agent to list available local models and request responses from a specific one.