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mcp-gtm-tech-stack-signal-scraper

Detect GTM Tech Stack

detect_gtm_tech_stack
Read-onlyIdempotent

Detects the GTM tech stack of any company from its public website, returning boolean flags for CRM and marketing automation tools like HubSpot, Salesforce, and Marketo.

Instructions

Detect which GTM tools a company uses from its public-facing website. Returns CRM, sequencer, and marketing automation signals as a flat, Clay-ready JSON row, with per-tool boolean flags for HubSpot, Salesforce, Apollo, Gong, Intercom, and Marketo, plus a composite tech stack signal. Read-only; requires an APIFY_TOKEN and consumes Apify credits per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesBare company domain without https:// and without a trailing slash. Example: stripe.com
crawl_additional_pagesNoIf true, crawls up to 2 additional pages per domain (pricing, product) to improve detection coverage. Slightly increases run time. Defaults to true when omitted.
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds non-obvious details: requires APIFY_TOKEN and consumes credits. No contradiction. The description complements the annotations well.

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 two sentences, front-loading the purpose and output, then adding requirements. Every sentence is informative. No wasted words.

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, the description explains the return format. It covers prerequisites (APIFY_TOKEN), cost (credits), and the two parameters are well-documented in the schema. No missing context for effective use.

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 both parameters have descriptions. The description does not add additional meaning beyond the schema, but it provides context about the output which indirectly relates to the domain parameter. Baseline 3 is appropriate.

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's purpose: detecting GTM tools from a company's website. It specifies the output as a flat, Clay-ready JSON row with per-tool boolean flags and a composite signal. This is a specific verb+resource, and with no sibling tools, differentiation is not needed.

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 provides clear usage context: it is read-only, requires an APIFY_TOKEN, and consumes Apify credits per call. It also implies this tool is for initial discovery. Since there are no sibling tools, explicit exclusion of alternatives is not required.

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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