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kouko

redshift-comment-mcp

by kouko
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

setup_via_dialog

Set up or update a Redshift connection profile by collecting host, user, and database name via chat, and password through a secure OS-native dialog that never transmits over MCP. Resolves 'not_configured' errors from other tools.

Instructions

Bootstrap (or update) a Redshift connection profile from inside an MCP session.

Use when DB tools (list_schemas etc.) return {"error": "not_configured"}, or to add a new profile / re-key an existing one. Ask the user for host / port / user / dbname conversationally — these are not secret — then call this tool. The password is collected via an OS-native dialog (macOS osascript / Linux zenity) launched server-side; it never crosses the MCP wire, never appears in chat or tool args.

Outcomes (return shape):

  • {"status": "configured", ...} — profile written, password in keychain. Lazy resolve picks it up on next DB tool call; no restart needed.

  • {"status": "dialog_cancelled" | "dialog_unavailable" | "platform_unsupported" | "empty_password", ...} — profile fields saved but no password set; the message field tells the agent / user what to do next (often: run redshift-comment-mcp set-password --profile X --stdin from a terminal).

For headless environments without a GUI, prefer the CLI pair set-fields + set-password --stdin instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostYes
portNo
userYes
dbnameYes
profileNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.6/5.0
Behavior5/5

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

Thoroughly explains password handling via OS dialog, never crossing MCP wire, and describes all possible outcomes. No annotations are provided, so the description carries the full burden and does so comprehensively.

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?

Description is well-structured with clear sections and front-loaded purpose, though slightly verbose. Every sentence adds value.

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

Completeness5/5

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

Given 5 parameters and an output schema, the description covers use case, outcomes, password safety, and alternatives completely. Output schema exists and description briefly explains return shapes.

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?

Schema coverage is 0%, but description adds context that host/port/user/dbname are conversational and not secret. However, it does not detail each parameter individually; defaults and types are only in 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?

Description clearly states it bootstraps or updates a Redshift connection profile, with specific verb and resource. It distinguishes from siblings by mentioning alternative tools for headless environments.

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

Usage Guidelines5/5

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

Explicitly says when to use (when DB tools return not_configured error) and when not (prefer set-fields + set-password in headless environments).

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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