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Agent.ai MCP Server

Agent.ai MCP Server

by OnStartups
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

company_research_v2_start_research

Initiate company research by providing a domain. Receive a report ID to track progress and retrieve results.

Instructions

Start researching a company by domain. Returns report_id for polling status.

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>",
      "output_variable_name": "<output_variable_name>"
    },
    "name": "company_research_v2_start_research"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYesDomain of the company to research (e.g., hubspot.com).
force_refreshNoSkip cache and regenerate the report.
output_variable_nameYesVariable name for the result. Access report_id with {{research_result.report_id}}.research_result

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to explain whether the research is synchronous/asynchronous, cache behavior (despite a 'force_refresh' parameter), error conditions, or side effects (e.g., overwriting previous reports).

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 extremely concise at 13 words across two sentences, immediately stating the action and key output. Every word earns its place with no fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite its conciseness, the description lacks completeness given the tool's role in a multi-step research workflow. It does not explain the research process, how to use the report_id, or confirm the polling pattern implied by 'for polling status,' leaving gaps for an AI agent unfamiliar with the sibling tools.

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?

All parameters are fully described in the input schema (100% coverage), so the description adds no additional meaning beyond the schema. The baseline of 3 applies as the description does not enhance understanding of the parameters.

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 action: 'Start researching a company by domain' and specifies the key return value 'Returns report_id for polling status,' which distinguishes it from related tools like 'get_report' or 'get_status' that handle completed results.

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

Usage Guidelines3/5

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

The description implies when to use (to initiate research) and hints at a follow-up polling pattern via 'report_id for polling status,' but it does not explicitly state when not to use this tool or mention alternatives among the many similar research tools in the sibling list.

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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