Route prompts to local AI models via Ollama through an MCP interface.
npx skills add https://github.com/bryancostanich/Cercano --skill cercano-local
Please help me install this Agent Skill. Skill: cercano-local Source: https://github.com/bryancostanich/Cercano/tree/main/plugins/skills/cercano-local Command: npx skills add https://github.com/bryancostanich/Cercano --skill cercano-local
Cercano Local Inference enables running prompts against local AI models through Cercano's MCP interface, leveraging Ollama for private, fast on-device inference.
Prompt Cercano to run a local inference on your data using Ollama and return the results.
High-intent search queries and answers about installing and using this skill.
Run local inference by routing prompts through a Cercano server connected to an Ollama instance, which processes your requests entirely on-device for fast, private responses without cloud round-trips.
Yes, Ollama supports agentic code generation through a generate-validate loop that executes code locally, writes changes directly to disk, and validates the results on your hardware.
An MCP interface routes local AI model requests by acting as a bridge between your prompts and a locally hosted Ollama backend, managing the inference execution and returning results privately.
Yes, you need a Cercano server connected to an Ollama instance to route requests to local inference, exposing the MCP interface needed to process chat prompts and agentic workflows.
Yes, local-first routing primarily targets on-device Ollama inference but includes optional remote fallbacks to support larger AI models that exceed your local hardware capacity.
Limitations of local agentic code generation include hardware constraints affecting model size and speed, though optional remote fallbacks can mitigate capacity limits for larger models.
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