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Glama

Agent Broker

by dev.hatchloop

call_business

Destructive

Place a conversational voice-AI phone call to a business on a consumer's behalf and return a structured answer. THE differentiated capability: reach the tens of millions of long-tail SMBs that have NO API and NO booking page — only a phone number. An AI agent cannot pick up a phone and hold a conversation; this tool does. Give a plain-language objective; the voice AI navigates the call and extracts the answer. Business-directed (B2B), far less restricted than calling consumers — but the compliance gate still enforces recording consent per jurisdiction. Async: returns a call handle; poll get_outcome for the transcript + extracted fields.

WHEN TO USE: Use when the target business has NO booking URL and NO API — only a phone number — and the consumer asked the agent to reach them (e.g. 'call this plumber and ask if they can come Tuesday', 'ask the salon if they take walk-ins this afternoon'). Also use to confirm details a booking page doesn't expose (real-time availability, custom quotes). WHEN NOT TO USE: Do NOT use when the business has a booking URL — use import_booking_url + schedule_appointment (cheaper, faster, deterministic). Do NOT use for calls to consumers/individuals (this tool is for reaching businesses). Do NOT use for marketing or telemarketing — the compliance gate and the B2B-only framing reject that. COST: $0.2 per_call LATENCY: ~45000ms EXECUTION: async_by_default (use get_outcome to retrieve result)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
smb_idNoKnown SMB identifier with a phone on record. Provide this OR business_phone.
objectiveYesWhat the call should accomplish, in plain language.
country_codeNoISO 3166-1 alpha-2 for compliance + recording-consent routing.
on_behalf_ofNoName of the consumer the call is placed for.
business_phoneNoBusiness phone in E.164 (e.g. +14045550123). Provide this OR smb_id.
extract_fieldsNoStructured fields to pull from the answer, e.g. ['available_tomorrow','price_quote','earliest_slot'].
idempotency_keyNoOptional client-supplied key for safe retries. Replaying the same key within 24h returns the original receipt - the operation is NOT re-executed and NOT re-charged.
max_duration_secondsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / idempotency_key
      Added value: +{
+  "description": "Optional client-supplied key for safe retries. Replaying the same key within 24h returns the original receipt - the operation is NOT re-executed and NOT re-charged.",
+  "maxLength": 128,
+  "type": "string"
+}
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Even with annotations present, the description adds substantial behavioral context: async execution via call handle requiring poll of get_outcome, compliance consent enforcement per jurisdiction, B2B-only restriction, idempotency-key retry semantics, cost, and latency. No contradictions with the annotations were found.

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 well-structured with clear sections (WHEN TO USE, WHEN NOT TO USE, COST, LATENCY, EXECUTION) and is front-loaded with the core purpose. Each section contributes selection or invocation-relevant information, and the redundancy is minimal and reinforcing.

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

Completeness5/5

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

For a tool with 8 parameters, an async execution model, and no output schema, the description is remarkably complete: it explains expected return via get_outcome, cost, latency, compliance gate, and the boundary conditions against sibling tools. An agent has what it needs to select and call this tool 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?

Schema coverage is 88%, so the schema already explains most parameters. The description adds illustrative plain-language objective examples and mentions structured extraction, but it does not deeply define smb_id, business_phone, country_code, or extract_fields beyond the schema, which is acceptable given the high schema coverage.

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 first sentence names a specific verb+resource ('Place a conversational voice-AI phone call to a business') and the return type ('structured answer'). It also differentiates from siblings by emphasizing it is for businesses with no API and no booking page, making its role distinct from import_booking_url and schedule_appointment.

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

Usage Guidelines5/5

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

The WHEN TO USE and WHEN NOT TO USE sections are explicit: use for businesses with only a phone number, do not use when a booking URL exists (and names the alternatives), do not use for consumers, and do not use for marketing. This gives an agent unambiguous selection criteria.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools target distinct resource+action pairs (find_business vs verify_business, check_booking_link vs import_booking_url, get_status vs get_outcome). The main confusable pairs are send_message vs send_transactional_confirmation and verify_business vs verify_company_record, but their descriptions draw clear boundary lines.

Naming Consistency4/5

The set overwhelmingly follows lower_snake_case verb_noun naming (call_business, check_quota, find_business, send_message, verify_company_record). Minor deviations like self_test and mint_key, plus inconsistent verb choices (lookup_ vs get_ vs find_), prevent a perfect score.

Tool Count3/5

At 23 tools, the server falls into the heavy range and bundles several unrelated domains: SMB booking/messaging, trade and sanctions compliance, company verification, and platform operations. Each tool is individually reasonable, but the set feels like multiple servers merged into one.

Completeness3/5

Core SMB workflows are well covered: find/verify/import/book, messaging with conversation handling, and compliance preflights. Notable gaps include no consent-record management even though send_message requires consent_record_id for marketing, no update/delete lifecycle for leads or businesses, and no webhook configuration despite webhooks being referenced.

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