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databar-ai

Databar MCP Server

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by databar-ai

add_table_waterfall

Add a waterfall enrichment to a table, cascading through multiple data providers sequentially until a result is found.

Instructions

Add a waterfall to a table. A waterfall tries multiple data providers in sequence until one returns a result.

WORKFLOW:

  1. Call search_waterfalls to find the right waterfall (e.g. "email_getter", "person_getter").

  2. Note the waterfall identifier, available_enrichments (provider IDs), and input_params.

  3. Call get_table_columns to see available column names.

  4. Build the mapping: keys are waterfall param names, values are column names.

  5. The returned id is the TABLE-WATERFALL id — use it with run_table_enrichment to trigger a run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_uuidYesThe UUID of the table
waterfall_identifierYesThe waterfall identifier (e.g. "email_getter"). Get from search_waterfalls.
enrichmentsYesList of enrichment (provider) IDs to use in the waterfall cascade. Get from search_waterfalls available_enrichments.
mappingYesMaps waterfall param names to table column names. Keys = param names from waterfall input_params. Values = column names from get_table_columns.
email_verifierNoOptional enrichment ID for email verification (only for email waterfalls with is_email_verifying=true).
Behavior4/5

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

No annotations are present, so description carries full burden. It explains the waterfall behavior (tries providers in sequence) and the nature of the returned id (table-waterfall id, not a run). It does not mention error handling or side effects, but the core behavioral traits are covered. Score reduced slightly for missing potential failure modes.

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 includes a numbered workflow block that is useful but somewhat lengthy. It is well-structured with clear steps. Could be slightly more concise, but every sentence earns its place.

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 no output schema, description explains the return value (table-waterfall id). It also covers the full workflow from search to run, making the tool self-contained. Sibling tools are numerous, but the description provides enough context to differentiate and use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds significant value beyond schema: it explicitly tells where to obtain each parameter (e.g., enrichments from search_waterfalls, mapping from get_table_columns). This context is crucial for correct usage and is not present in the schema alone.

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 'Add a waterfall to a table' and explains that a waterfall tries multiple providers in sequence. It distinguishes from siblings by detailing a unique workflow involving search_waterfalls and get_table_columns, which are not required for similar tools like add_table_enrichment.

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?

Explicit workflow steps are provided (1-5), including prerequisites and post-conditions. It guides when to use this tool (after search_waterfalls and get_table_columns) and what to do with the returned id (use with run_table_enrichment). No confusion with 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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