add-ollama-tool

Integrate local Ollama models into a container agent via MCP server.

Updated Mar 11, 2026
One-click install
npx skills add https://github.com/mbaker95/nanodex --skill add-ollama-tool-mbaker95
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: add-ollama-tool
Source: https://github.com/mbaker95/nanodex/tree/main/.agents/skills/add-ollama-tool
Command: npx skills add https://github.com/mbaker95/nanodex --skill add-ollama-tool-mbaker95

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill enables the container agent to leverage local Ollama models for cost-effective and faster AI tasks like summarization, translation, and general queries, reducing reliance on external APIs.

Core Features & Use Cases

  • Local Model Integration: Connects to a local Ollama MCP server.
  • Tool Exposure: Provides ollama_list_models and ollama_generate tools for the agent.
  • Use Case: Offload tasks like summarizing long documents or translating text to your local Ollama instance instead of using a cloud-based LLM, saving costs and improving response times.

Quick Start

Send a message like "use ollama to tell me the capital of France".

Frequently Asked Questions about add-ollama-tool

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate local Ollama models into my agent for AI tasks?▼

You can integrate local Ollama models by adding an MCP server, which exposes tools like ollama_list_models and ollama_generate for the container agent to handle text generation and summarization.

What are the prerequisites for using local Ollama models with an MCP server?▼

To use local Ollama models, Ollama must be installed and actively running on your host system before the container agent can connect to the MCP server.

Can I use local models to offload summarization tasks instead of external APIs?▼

Yes, you can offload summarization and translation tasks to a local Ollama instance, reducing reliance on external APIs to save costs and improve response times.

What tools are exposed when connecting to a local Ollama MCP server?▼

Connecting to a local Ollama MCP server exposes two primary tools: ollama_list_models to view available models and ollama_generate to execute text prompts.

What is the best way to reduce external LLM costs for general queries?▼

Using a local Ollama instance is an effective way to reduce external LLM costs, allowing the container agent to handle general queries and code generation without external API calls.