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pghdma

CallRail MCP

list_text_messages

Retrieve a paginated list of SMS conversations sent or received via CallRail tracking numbers, filterable by company and date range.

Instructions

List SMS/text message conversations sent to or received via CallRail trackers. Paginated. Filterable by company and date window.

Receiving SMS works on standard accounts. Outbound SMS sending requires CallRail's A2P SMS API permission (returns 403 otherwise); see create_text_message notes if available on your plan.

Args: account_id: CallRail account ID. Auto-resolves if omitted. company_id: Filter to one company. Omit for all companies. days: Lookback in days (default 7). Ignored if start_date provided. start_date: 'YYYY-MM-DD'. end_date: 'YYYY-MM-DD' (defaults to today). per_page: Page size (max 250). page: 1-indexed.

Returns: JSON string with page, per_page, total_pages, total_records, and conversations[]. Each conversation has a list of inbound + outbound messages, customer phone number, the tracking number used, and timestamps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
pageNo
end_dateNo
per_pageNo
account_idNo
company_idNo
start_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description covers pagination, auto-resolution of account_id, date window behavior, and return format. It notes potential 403 errors for missing A2P permission, but lacks explicit read-only declaration or rate limits.

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?

Well-structured with clear one-liner, organized Args and Returns sections. Every sentence adds value; no fluff or repetition.

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 tool with 7 parameters and output schema, the description covers pagination, filtering, and permission notes. Could include more edge cases (e.g., empty results) or detailed conversation structure, but adequate overall.

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 description coverage is 0%, but the description fully documents all 7 parameters, including defaults, format, and behavior (e.g., days ignored if start_date provided). Adds significant semantic value beyond schema.

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 it lists SMS/text message conversations via CallRail trackers, with pagination and filtering. It distinguishes from siblings like get_text_message (single message) and list_calls (calls).

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 explains when to use (listing messages) and mentions prerequisites (A2P permission for outbound) and references create_text_message for more info. It does not explicitly name alternatives but context is clear.

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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