MCP Server Generator

get_tool_info

Retrieve tool details at summary or full level to understand its use cases and capabilities.

Instructions

Get information about a specific tool with progressive disclosure

Args: tool_name: Name of the tool to get information about detail_level: Level of detail: - "summary": Name, description, and category - "full": Complete information including use cases and full description

Returns: JSON string with tool information at requested detail level

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tool_name": "<tool_name>"
    },
    "name": "get_tool_info"
  }
}

Input Schema

Name	Required	Description	Default
`tool_name`	Yes
`detail_level`	No		summary

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 29, 2026

TDQS

A4.1/5.0

Behavior3/5

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

With no annotations, the description bears full burden. It discloses the return format (JSON string) and detail_level content, but does not mention error cases, required permissions, or potential pitfalls. Adequate for a simple read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with an opening line and Args/Returns sections. It is concise but not overly terse, providing necessary detail without extraneous words.

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 tool's simplicity (2 params, no annotations, output schema present), the description adequately covers purpose, parameters, and return details. It lacks error handling or exact match requirements but is sufficient for effective use.

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?

Schema description coverage is 0%, so the description compensates by explaining both parameters: tool_name and detail_level with enum values. The description adds value beyond the schema's bare type definitions, especially for detail_level.

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 'Get information about a specific tool' with progressive disclosure, using a specific verb and resource. It distinguishes from siblings like search_tools by focusing on a single tool's details.

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 guidance on using detail_level enum (summary vs full) and what each returns. However, it does not explicitly compare to sibling tools like search_tools or get_best_practices, so the agent must infer when to use this tool over alternatives.

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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