io.github.Aguantar/clickhouse-dataops-mcp

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ch_list_tables

List all tables in a ClickHouse database, including metadata like engine, keys, row count, disk size, and purpose descriptions. Start here to explore available data.

Instructions

List all tables with metadata and built-in descriptions.

Returns table name, engine type, partition/sorting keys, row count, disk size, and a human-readable description of each table's purpose. Use this as the starting point to understand what data is available.

Args: database: Database to list (default: cdc_pipeline)

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": "ch_list_tables"
  }
}

Input Schema

Name	Required	Description	Default
`database`	No		cdc_pipeline

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jun 3, 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 full burden. It discloses the return fields (row count, disk size, descriptions) but does not mention any side effects, permissions, or performance considerations, which is a gap for a read-only list 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?

The description is very concise: three sentences plus an Args line. No redundant information, and the purpose is front-loaded.

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?

The description covers the output fields well and provides context for usage. With an output schema present (not shown), the description completes the picture. However, it lacks mention of pagination or limits if there are many tables.

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?

The input schema has 0% description coverage, but the description provides the parameter name and default value ('database: Database to list (default: cdc_pipeline)'). This adds basic meaning beyond the schema, though it could include more details like valid database names or format.

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 the tool lists all tables with metadata and built-in descriptions, and positions it as a starting point. This distinguishes it from sibling ch_table_schema which likely focuses on a single table's schema.

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 advises to use this as a starting point to understand available data, implying it should be used before querying specific tables. However, it lacks explicit exclusions or comparison with alternatives like ch_table_schema.

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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