VideoNote-MCP

by HuangYincan

Overview Schema Source Related Servers Discussions Admin

Python

Local

list_providers

List configured LLM providers with their id, name, type, enabled status, and masked API key.

Instructions

列出已配置的 LLM 供应商（id、名称、类型、启用状态、api_key 掩码）。

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	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

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 of behavioral disclosure. It mentions 'api_key mask', which is a useful transparency detail, but omits any explicit read-only statement, authentication requirements, or side effects. The verb 'list' implies non-mutating, but lacks deeper 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?

One concise sentence, front-loaded with the action 'List' and immediately clarifies the resource and relevant fields. No superfluous content.

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?

For a simple list operation with 0 parameters and an output schema present, the description sufficiently covers what the tool does and the key attribute of the returned data (api_key mask). Missing explicit behavioral disclaimers, but overall adequate.

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, so the description has no parameter semantics to add. Baseline for 0 params is 4; the description is appropriately minimal.

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?

Description states 'List configured LLM providers' with fields, clearly distinguishing from sibling tools like add_provider, update_provider, and list_models. The verb 'list' is specific and the resource is explicit.

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?

Description implies usage for viewing providers but does not explicitly compare with alternatives like list_models or mention when not to use it. No exclusions or alternative tool references.

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