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easyonthesauce

elevenlabs-agents-mcp-server

List Recent Calls

elevenlabs_list_calls
Read-onlyIdempotent

List recent voice calls from ElevenLabs agents with optional filters by agent, outcome, or time range. Returns call details including status, duration, and direction.

Instructions

List recent conversations/calls, newest first, with optional filters.

Args:

  • agent_id (string, optional)

  • call_successful ('success' | 'failure' | 'unknown', optional)

  • call_start_after_unix / call_start_before_unix (number, optional)

  • page_size (1-100, default 30), cursor (string, optional)

Returns JSON: { calls: [{ conversation_id, agent_id, agent_name, status, call_successful, start_time_unix_secs, call_duration_secs, direction }], has_more, next_cursor }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoPagination cursor
agent_idNoFilter by agent
page_sizeNo
call_successfulNoFilter by evaluated call outcome
call_start_after_unixNoOnly calls starting after this unix timestamp (seconds)
call_start_before_unixNoOnly calls starting before this unix timestamp (seconds)
Behavior4/5

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

Annotations already declare readOnly and idempotent; description adds pagination details (has_more, next_cursor, ordering newest first) and return format, providing valuable context.

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 concise with clear Args and Returns sections, front-loaded with purpose, and no unnecessary content.

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?

With no output schema, the description fully explains the return structure, including call object fields, pagination. Annotations are rich, making the tool well-documented.

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 83%, so baseline is 3. Description provides concise summaries (e.g., default page_size) but does not add significant meaning 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 the tool lists recent conversations/calls, newest first, with optional filters. It distinguishes from siblings by specifying the resource and ordering.

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

Usage Guidelines3/5

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

The description implies when to use (listing calls) but does not explicitly mention when not to use or alternatives like get_call_report for details.

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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