leads-mcp

enrich-company

Get company intelligence from a domain — industry, size, funding, and tech stack — to qualify leads and personalize outreach.

Instructions

Get comprehensive company intelligence for a domain — industry, size, funding, tech stack, and more.

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": {
      "domain": "<domain>"
    },
    "name": "enrich-company"
  }
}

Input Schema

Name	Required	Description	Default
`domain`	Yes	Company domain (e.g., 'stripe.com')

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Aug 2, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the type of data returned (industry, size, funding, tech stack) but says nothing about data freshness, source, accuracy, or error behavior. This is a moderate level of transparency for a read-only enrichment tool but lacks detail on potential limitations.

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 a single sentence that front-loads the core action and resource, with no filler. It lists representative data fields to convey scope without wasting words.

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 one-parameter tool without an output schema, the description provides a solid overview of purpose and return categories. The phrase 'and more' leaves some ambiguity about the full set of fields, but the tool's simplicity and the listed examples make it sufficiently complete for an agent to invoke correctly.

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?

The input schema covers the only parameter with a description and example, achieving 100% coverage. The description adds 'for a domain' but does not provide additional semantic detail beyond what the schema already offers, so it stays at the baseline.

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 verb 'get' and resource 'comprehensive company intelligence' clearly state the tool's function. It explicitly scopes to a domain, and the example data fields (industry, size, funding, tech stack) distinguish it from sibling tools like enrich-person or find-email.

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 indicates the intended use case: when you have a domain and want company data. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an agent to know when to select this tool over siblings like search-companies (which requires search criteria rather than a specific domain).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server