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CallRail MCP

create_outbound_call

Place an outbound call by dialing from_number first, then bridging to to_number. confirm_dialing=True is required to execute. Returns call data.

Instructions

⚠️ Place an outbound call. THIS ACTUALLY DIALS A REAL PHONE.

CallRail will dial from_number first; once that's answered, it bridges to to_number. Both legs cost minutes against your bundle. Misuse can constitute unlawful telemarketing — verify consent.

You must pass confirm_dialing=True to actually place the call. This is a safety guard against accidental AI-driven cold-calls.

Args: from_number: Your end of the call (typically your tracking number, e.g. +14129548337). E.164 format. to_number: Recipient's number. E.164 format. confirm_dialing: REQUIRED — set True to actually dial. Returns error envelope if False (default). company_id: Optional company scope. account_id: Auto-resolves if omitted.

Returns: The call object CallRail creates (id, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_numberYes
to_numberYes
confirm_dialingNo
company_idNo
account_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Without annotations, the description fully discloses critical behavioral traits: the call is actually dialed, the call flow (dials from_number first, bridges to to_number), billing implications, and the safety guard. There is no contradiction with missing annotations.

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 informative but not overly verbose. It uses clear sectioning (warning, flow, safety, args, returns) and bold/emoji for emphasis. Every sentence adds value, though it could be slightly more concise.

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 complexity and presence of an output schema, the description covers purpose, parameters, safety, billing, legal disclaimer, and return value. It lacks mention of rate limits or prerequisites, but these are reasonable omissions for a well-documented tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description comprehensively documents each parameter: from_number and to_number with E.164 format and examples, confirm_dialing's role as a safety guard, and optional company_id/account_id. This adds significant meaning beyond the schema's minimal structure.

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: 'Place an outbound call' with a strong warning that it actually dials a real phone. It specifies the action (create), resource (call), and scope (outbound), distinguishing it from sibling tools like call_eligibility_check or update_call.

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 guidance on when to use the tool (to place an outbound call) and emphasizes a safety guard ('You must pass confirm_dialing=True'). It warns against misuse and unlawful telemarketing, but does not explicitly name alternative tools for similar tasks.

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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