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MySQL MCP by InsightfulPipe

by com.insightfulpipe
OverviewDiscussionsAdmin

mysql Prompts

prompts_menu
Read-only

Access mysql prompt catalog with 4 operations:

  1. List Public Prompts: • request='menu' - No additional params needed • Returns: All public/system prompts available for mysql

  2. List Custom Prompts: • request='menu', prompt_type='custom', workspace_id= • Returns: All custom prompts for the specified workspace

  3. Get Public Prompt Details: • request='prompt_details', prompt_id= • Returns: Full text/details of a public prompt

  4. Get Custom Prompt Details: • request='prompt_details', prompt_id=, is_custom=True, workspace_id= • Returns: Full text/details of a custom prompt

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": {
      "request": "<request>"
    },
    "name": "prompts_menu"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestYes
is_customNo
prompt_idNo
prompt_typeNo
workspace_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

The readOnlyHint annotation already establishes that this is a safe read operation, and the description adds useful context about what each operation returns. It does not disclose authentication requirements, rate limits, or other behavioral constraints beyond the annotation.

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 operation list is front-loaded, clearly structured, and each bullet adds actionable parameter and return information without filler.

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 read-only annotation and the presence of an output schema, the description covers enough for correct invocation across all four operations. It is slightly incomplete because it does not mention sibling-tool alternatives or failure behavior.

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 must carry parameter meaning; it does this well by mapping request, prompt_type, workspace_id, prompt_id, and is_custom to the four operations. Minor gaps remain because it does not discuss parameter defaults or error conditions.

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?

The description states a specific resource ('mysql prompt catalog') and enumerates four distinct operations, making the tool's overall purpose clear. It does not explicitly differentiate this tool from its siblings, which keeps it from a 5.

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 gives explicit parameter combinations for listing vs. getting details and for public vs. custom prompts, so an agent can select the right operation. It does not state when to prefer this tool over sibling tools such as query_contexts or query_data.

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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