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francestudent-mcp

francestudent-mcp

by Yormede
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Agents France Student

fs_list_agents

Lists the AI agents available on your France Student IA account, identifying which OpenAI models can generate images.

Instructions

Liste les agents (modèles) disponibles sur ton compte. Seuls les agents OpenAI savent générer des images.

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": "fs_list_agents"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose one real behavioral trait beyond the name: only OpenAI agents can generate images. It says nothing about whether the call requires authentication, whether the list is paginated, or what the returned entries look like, which leaves gaps for a discovery tool.

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?

Two short sentences, front-loaded with the action and resource, then the one capability fact that affects downstream choice. Nothing is padded or redundant.

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

Completeness3/5

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

For a zero-parameter read tool with no output schema and no annotations, the description is workable but thin: it never indicates what identifying fields an agent entry exposes (name, id, model type), which an agent needs in order to pass the right value to fs_generate_image.

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 takes zero parameters, so the schema is trivially complete and the description needs to add nothing. Baseline 4 applies; the note about account scoping is a minor bonus.

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

Purpose4/5

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

"Liste les agents (modèles) disponibles sur ton compte" gives a specific verb plus resource and clarifies that "agents" means models. It separates itself from fs_generate_image by noting which agents can produce images, though it never names fs_usage or other siblings explicitly.

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?

Usage is only implied: an agent can infer it should call this to discover available models before generating images. There is no explicit when-to-use statement, no exclusion, and no reference to the sibling tools by name.

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

Deploy Server

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