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Databar MCP Server

Databar MCP Server

Official
by databar-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_table_waterfalls

Retrieve all installed waterfall IDs for a table to use with data enrichment execution.

Instructions

List all waterfalls installed on a table. Returns waterfall IDs that can be used with run_table_enrichment.

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": {
      "table_uuid": "<table_uuid>"
    },
    "name": "get_table_waterfalls"
  }
}

Input Schema

NameRequiredDescriptionDefault
table_uuidYesThe UUID of the table

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It only states it 'lists all waterfalls' and returns IDs, but omits details like error handling, permissions, or whether the list is paginated. This is minimal disclosure.

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 concise with two sentences. It is front-loaded with the key action and adds a practical note about output usage. No redundant information is present.

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 listing tool with one parameter and no output schema, the description covers what the tool does and what it returns. It lacks details on edge cases or output format, but these are minor omissions for this tool's complexity.

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?

With 100% schema description coverage, the schema already describes the parameter. The description adds no extra meaning beyond the schema, so it meets the baseline but does not enhance parameter understanding.

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 waterfalls on a table, with a specific verb and resource. It distinguishes from sibling tools like 'add_table_waterfall' and 'run_table_enrichment' by indicating the output can be used with the latter.

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?

The description implies usage by stating the output is for use with 'run_table_enrichment', but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among siblings.

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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