Skip to main content
Glama

ollama_list_models

Read-onlyIdempotent

Discover installed Ollama models and their memory status to identify available options before using chat or generation tools.

Instructions

List all Ollama models installed on the local machine with their memory load status. Use this tool to discover available model names before calling ollama_chat, ollama_generate, or ollama_show_model. Do not use this to check if the Ollama daemon is running — use ollama_health instead. Behavior: Read-only, idempotent, safe to retry. No authentication required. No rate limits. Returns an empty models array if no models are installed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYesAll locally installed models. Empty array if none are installed.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds valuable behavioral context beyond annotations: it specifies 'No authentication required' and 'No rate limits' (not covered by annotations), and clarifies the return behavior ('Returns an empty models array if no models are installed'). While annotations already cover readOnlyHint, destructiveHint, and idempotentHint, the description provides additional operational details that help the agent understand execution context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with zero wasted sentences. The first sentence states the core purpose, the second provides usage guidance with specific sibling references, and the third adds behavioral details. Every sentence earns its place by adding distinct value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, read-only operation) and the presence of comprehensive annotations and output schema, the description provides complete contextual information. It covers purpose, usage guidelines, behavioral traits, and distinguishes from siblings—everything needed for an agent to correctly select and invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters and 100% schema description coverage, the baseline would be 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on the tool's purpose and behavior. No parameter information is needed or missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the verb ('List') and resource ('all Ollama models installed on the local machine'), including the specific scope ('with their memory load status'). It clearly distinguishes from siblings by naming specific alternative tools (ollama_chat, ollama_generate, ollama_show_model) and contrasting with ollama_health.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('to discover available model names before calling ollama_chat, ollama_generate, or ollama_show_model') and when not to use it ('Do not use this to check if the Ollama daemon is running — use ollama_health instead'). It names specific alternative tools for different purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/VrtxOmega/Ollama-Omega'

If you have feedback or need assistance with the MCP directory API, please join our Discord server