@aiwerk/mcp-server-elevenlabs

create_batch_call

Submits batch call requests to multiple recipients with a chosen agent, supporting scheduling, WhatsApp parameters, telephony configuration, and concurrency limits.

Instructions

Submit A Batch Call Request.

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": {
      "call_name": "<call_name>",
      "agent_id": "<agent_id>",
      "recipients": "<recipients>"
    },
    "name": "create_batch_call"
  }
}

Input Schema

Name	Required	Description	Default
`agent_id`	Yes
`timezone`	No
`branch_id`	No
`call_name`	Yes
`recipients`	Yes
`environment`	No
`whatsapp_params`	No
`scheduled_time_unix`	No
`agent_phone_number_id`	No
`telephony_call_config`	No
`target_concurrency_limit`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

C2/5.0

Behavior2/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false, and destructiveHint=false, covering the basic safety profile. The description adds no behavioral context beyond 'submit'—it does not mention side effects, required permissions, return behavior, or whether the batch is queued immediately.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is concise in form but severely under-specified for a tool with 11 parameters and nested configuration. The sentence does not earn its place with useful information, making this under-specification rather than effective conciseness.

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

Completeness1/5

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

For a complex batch-call creation tool with 11 parameters, nested objects, no output schema, and only minimal annotations, the one-line description is completely inadequate. An agent cannot reliably determine required inputs, scheduling behavior, or provider-specific options from the description alone.

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

Parameters1/5

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

Schema description coverage is 0% for 11 parameters, including required ones like agent_id and recipients plus nested objects such as telephony_call_config and whatsapp_params. The description provides no parameter meaning whatsoever, failing to compensate for the complete lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb 'Submit' and resource 'Batch Call Request', so the general purpose is identifiable. However, it offers no detail about what a batch call is, how it differs from sibling operations like cancel_batch_call or retry_batch_call, and reads close to a restatement of the tool name.

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

Usage Guidelines2/5

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

Provides no guidance on when to use this tool versus alternatives such as cancel_batch_call, get_batch_call, or get_workspace_batch_calls. No prerequisites, context, or exclusions are mentioned, leaving the agent to infer usage entirely.

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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