openwebui-mcp-server

openwebui_list_models

List all available models in Open WebUI, including Ollama local, OpenAI, and custom pipe models, with IDs, names, and sources.

Instructions

List all available models in Open WebUI — includes Ollama local models, OpenAI models, and custom pipe models. Returns model IDs, names, and sources.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "openwebui_list_models"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.2Aug 10, 2026

TDQS

A4.5/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates this is a read-only listing operation and discloses what the tool returns (model IDs, names, sources). While it does not mention authentication or pagination, these are not critical for a simple list tool, and the behavior is transparent enough.

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 a single, well-structured sentence that front-loads the core purpose, lists inclusions, and states return fields. Every phrase adds value, with no fluff or repetition.

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?

For a simple parameterless list tool with no output schema, the description is fully complete. It explains what models are included and what information is returned, which is all the agent needs to invoke the tool correctly. No additional context is necessary.

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?

The tool has zero parameters, and the schema is empty with 100% coverage. Per the baseline rule for 0 params, a score of 4 is appropriate. The description adds no parameter details because none exist, and the schema already covers everything.

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 clearly states the tool's action ('List all available models'), specifies the resource (models in Open WebUI), and distinguishes it from sibling tools by enumerating the model sources (Ollama, OpenAI, custom pipes). This is a specific verb+resource with clear scope.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool (to retrieve available models), and sibling tools are all for different resources (chats, knowledge, files, functions, prompts), so there is no ambiguity. However, it does not explicitly mention alternatives or exclusion cases, so it falls short of a 5.

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