OutreachPilot MCP Server

run_research

Launch agentic research to find companies or people matching your criteria. Get a cost estimate first, then confirm to execute and receive a job ID for status polling.

Instructions

Start an agentic research job to find companies or people matching your criteria. Returns a job_id to poll with check_research_status. Send with confirmed=false first to get a cost estimate, then confirmed=true to execute.

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": {
      "query": "<query>"
    },
    "name": "run_research"
  }
}

Input Schema

Name	Required	Description	Default
`depth`	No	Research depth: 'standard' (2 credits/result), 'thorough' (3), or 'deep' (5). Default: standard.	standard
`limit`	No	Max results to find. Default 10, max 50.
`query`	Yes	Natural language search criteria (e.g. 'fintech founders in NY', 'SaaS companies with 50-200 employees').
`confirmed`	No	Set to false for cost estimate, true to execute. Always get estimate first.
`target_type`	No	What to search for: 'companies' or 'people'. Default: companies.	companies
`idempotency_key`	No	Optional stable key to prevent duplicate research job creation on retries.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Aug 9, 2026

TDQS

A4.4/5.0

Behavior5/5

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

With no annotations provided, the description carries full behavioral disclosure. It reveals the async job nature, the required two-step confirmation, and the polling requirement via check_research_status. This is substantial context beyond what the schema provides.

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 sentences, front-loaded with the main action, and every sentence earns its place. No redundant phrases.

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?

Covers the async job execution, job_id return, polling, and the confirmation workflow. However, it doesn't describe what the results will look like (though that may be delegated to check_research_status) or cost estimate details, leaving minor ambiguity given there is no output schema.

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% for all 6 parameters, so the baseline is 3. The description reinforces the confirmed=false-first workflow, but this is already clearly documented in the schema, so it adds little new parameter-level meaning.

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 starts an agentic research job to find companies or people. It distinguishes itself from the sibling check_research_status by noting it returns a job_id to poll, making its role in the workflow explicit.

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?

Provides a clear two-step usage sequence: send with confirmed=false for a cost estimate, then confirmed=true to execute. While it doesn't explicitly name alternatives or when not to use, the workflow is very specific and actionable.

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