LLM Provider Intelligence

list_providers

List LLM providers with their capabilities, pricing, and agent scores. Filter by specific requirements.

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_providers"
  }
}

Input Schema

Name	Required	Description
`best_for`	No	Filter by use case: tool_calling, reasoning, cost, speed, long_context, rag
`max_price`	No	Max input price per million tokens
`x402_native`	No	Only show x402-native providers
`tool_calling`	No	Only show providers with tool calling

Schema Changelog

Changes observed during successful MCP inspections.

First observedJun 12, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are present, so the description carries full burden. It communicates a read-like operation ('List') and what data is returned, but does not disclose any additional behavioral traits such as pagination, rate limits, or authentication requirements.

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, clear sentence followed by a concise filter note. Every word earns its place with no redundancy.

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?

The tool is simple with four optional, well-documented parameters and no output schema. The description adequately covers the return content (capabilities, pricing, agent scores) and the filtering capability. Sibling tools exist but their absence from the description does not create a critical gap.

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?

The schema provides 100% coverage with detailed descriptions for all four parameters. The description only generically mentions filtering and adds no new parameter-specific meaning beyond the schema.

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 uses the specific verb 'List' and clearly identifies the resource 'LLM providers' along with the included attributes (capabilities, pricing, agent scores). This distinguishes it from siblings 'check_provider_status' and 'recommend_llm'.

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

Usage Guidelines3/5

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

The description implies usage through 'Filter by specific requirements' but does not explicitly state when to use this tool versus the alternatives. No exclusions or named alternatives are provided.

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

All LLM Provider Intelligence tools Inspect

Try in Browser

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?