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explorium-ai

Explorium AgentSource MCP Server

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by explorium-ai

enrich_businesses_technographics

Retrieve the complete technology stack and categorized technographics (e.g., sales, marketing, devops) for bulk businesses.

Instructions

Get technographics data in bulk.
Returns:
- Full technology stack used by the business
- Nested technology stack categorized by function (e.g., Sales, Marketing, DevOps)
- Detailed breakdown by categories including:
  - Testing and QA tools
  - Sales software
  - Programming languages and frameworks
  - Productivity and operations tools
  - Product and design software
  - Platform and storage solutions
  - Operations software
  - Operations management tools
  - Marketing technologies
  - IT security solutions
  - IT management systems
  - HR software
  - Health tech applications
  - Finance and accounting tools
  - E-commerce platforms
  - DevOps and development tools
  - Customer management systems
  - Computer networks
  - Communications tools
  - Collaboration platforms
  - Business intelligence and analytics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
business_idsYesList of Explorium business IDs from match_businesses
Behavior2/5

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

With no annotations, the description must disclose all behavioral traits. It only implies a read operation ('Get ... data') and does not mention authentication, rate limits, data freshness, or potential side effects. The extensive output description does not compensate for missing behavioral context.

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 front-loaded with the purpose and then provides a structured list of return categories. While the list is long, it is directly useful for an agent to understand output content. It could be more concise but is not verbose.

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?

Given the absence of an output schema, the description thoroughly explains the return value structure with 21 categories. It covers the essential information needed to use the tool. However, it lacks context on error handling, limits, and data recency.

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 100% and the parameter 'business_ids' has a description. However, the tool description adds no new meaning beyond the schema's description. Baseline score of 3 is appropriate as it neither improves nor degrades 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 starts with 'Get technographics data in bulk,' which clearly specifies the verb 'get' and the resource 'technographics data.' The detailed list of categories distinguishes it from other enrich tools like enrich_businesses_firmographics or enrich_businesses_financial_metrics. It is specific and unambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus its siblings. The description does not mention prerequisites, alternatives, or scenarios where this tool is preferred. The agent must infer usage from the tool name alone.

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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