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mcp-llm-gateway

mcp-llm-gateway

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_models

List all models from your configured LLM providers. Use optional provider filter to focus on a single provider.

Instructions

List all available models from the configured providers.

Fetches models from the configured providers, with caching. Can filter by provider ID.

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": "list_models"
  }
}

Input Schema

NameRequiredDescriptionDefault
providerNoOptional provider ID to filter models.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses caching and fetching from providers, but does not mention any side effects, rate limits, authentication, or whether it is read-only. The caching behavior is helpful 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 two sentences long, front-loaded with the main purpose, and every word adds value. No fluff or unnecessary repetition.

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

Completeness4/5

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

Given the simplicity of the tool (single optional parameter, output schema exists), the description adequately covers the key aspects: listing models, caching, and filtering. However, it does not mention any pagination, limits, or ordering, which could be useful for completeness.

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

Parameters3/5

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

Schema description coverage is 100%, with the parameter already described as 'Optional provider ID to filter models.' The description adds minimal extra value ('Can filter by provider ID'), so the baseline score of 3 is appropriate.

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 verb 'List' and the resource 'all available models from the configured providers'. It distinguishes itself from the sibling tool 'complete' by focusing on listing models, which is a different operation.

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 mentions caching and the ability to filter by provider ID, giving context for usage. It implicitly tells when to use this tool (to list models) vs the sibling 'complete' (likely for completions), but lacks explicit exclusions or alternative conditions.

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

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