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databar-ai

Databar MCP Server

Official
by databar-ai

search_exporters

Find the right data exporter for pushing data to external services like Google Sheets, HubSpot, or Salesforce. Search by query and get matching exporters with IDs and descriptions.

Instructions

Search and discover available data exporters (CRM/destination integrations). Use this to find the right exporter for pushing data to external services (e.g., "Google Sheets", "HubSpot", "Salesforce"). Returns a list of matching exporters with their IDs and descriptions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query to find exporters (e.g., "google sheets", "hubspot", "salesforce", "crm")
limitNoMaximum number of results to return (default: 10)
Behavior4/5

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

No annotations provided. Description discloses that it returns 'a list of matching exporters with their IDs and descriptions'. Does not mention any destructive side effects; it is a read-only search. Could be improved by noting search behavior (e.g., case sensitivity, matching fields) but adequate.

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?

Two concise sentences, no redundancy. First sentence states purpose, second provides usage context and return info. Front-loaded with key action and resource.

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 compensates by stating return content. Parameters are well-documented with examples. Sufficient for an agent to understand and invoke the tool correctly.

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 coverage is 100% (both parameters have descriptions). The description adds value by including example queries (e.g., 'google sheets', 'hubspot') and specifying the default limit. Also states the return format (list with IDs and descriptions), which is not 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 'search and discover available data exporters (CRM/destination integrations)' with specific examples like 'Google Sheets', 'HubSpot', 'Salesforce'. Differentiates from siblings like 'search_enrichments' and 'search_waterfalls' by focusing on exporters for pushing data to external services.

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?

Explicitly says 'Use this to find the right exporter for pushing data to external services' and provides example queries. Does not explicitly state when not to use or mention alternatives, but context implies use for discovery rather than detail retrieval.

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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