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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

get_conversation_histories_route

Read-onlyIdempotent

Retrieve ElevenLabs conversation histories with filters for agent, user, tags, topics, ratings, dates, duration, status, and transcript search. Supports pagination and summary inclusion.

Instructions

Get Conversations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoUsed for fetching next page. Cursor is returned in the response.
searchNoFull-text or fuzzy search over transcript messages
tag_idsNoFilter conversations by conversation tag IDs assigned via the conversation-tags endpoints.
user_idNoFilter conversations by the user ID who initiated them.
agent_idNoAgent id (agent_…) or speech engine external id (seng_), resolved to the same underlying resource.
branch_idNoFilter conversations by branch ID.
page_sizeNoHow many conversations to return at maximum. Can not exceed 100, defaults to 30.
text_onlyNo
topic_idsNoFilter conversations by topic IDs assigned during topic discovery.
rating_maxNoMaximum overall rating (1-5).
rating_minNoMinimum overall rating (1-5).
tool_namesNoFilter conversations by tool names used during the call.
version_idNoFilter conversations by version ID.
summary_modeNoWhether to include transcript summaries in the response.
main_languagesNoFilter conversations by detected main language (language code).
sort_directionNoThe direction to sort conversations by call start time. Defaults to descending (newest first).
call_successfulNoThe result of the success evaluation
guardrail_typesNoFilter to conversations where a guardrail of any of these types triggered (metadata.triggered_guardrails.guardrail_type). Repeat param to match any of several.
exclude_statusesNoExclude conversations with the given statuses. Useful for hiding in-progress / processing conversations from list views.
evaluation_paramsNoEvaluation filters. Repeat param. Format: criteria_id:result. Example: eval=value_framing:success
visited_agent_idsNoFilter conversations where any of these agents participated. Can not exceed 50 values.
tool_names_erroredNoFilter conversations by tool names that had errored calls.
data_collection_idsNoData collection field IDs to include in each conversation summary. Repeat param. When omitted, data_collection_results is not returned.
termination_reasonsNoFilter conversations by their stored termination_reason (metadata.termination_reason). Repeat param to match any of several.
has_feedback_commentNoFilter conversations with user feedback comments.
call_start_after_unixNoUnix timestamp (in seconds) to filter conversations after to this start date.
tool_names_successfulNoFilter conversations by tool names that had successful calls.
call_duration_max_secsNoMaximum call duration in seconds.
call_duration_min_secsNoMinimum call duration in seconds.
call_start_before_unixNoUnix timestamp (in seconds) to filter conversations up to this start date.
custom_guardrail_namesNoFilter to conversations where a custom guardrail with any of these names triggered (metadata.triggered_guardrails.guardrail_name). Only custom guardrails carry a name. Repeat param to match any of several.
data_collection_paramsNoData collection filters. Repeat param. Format: id:op:value where op is one of eq|gt|gte|lt|lte|missing.
parent_conversation_idNoFilter conversations by parent conversation ID for subagent conversations.
dynamic_variable_paramsNoDynamic variable filters. Repeat param. Format: name:op:value where op is one of eq|gt|gte|lt|lte. Comparison operators require a numeric value. Names containing ':' cannot be expressed.
evaluation_criteria_idsNoEvaluation criteria IDs to include in each conversation summary. Repeat param. When omitted, evaluation_criteria_results is not returned.
triggered_procedure_idsNoFilter conversations where any of these procedures were triggered. Can not exceed 50 values.
visited_agent_branch_idsNoFilter conversations where any of these agent branches participated. Can not exceed 50 values.
workflow_node_entered_idNoFilter conversations to only those that entered the given node.
conversation_product_typeNoRestrict results to a single conversation product surface.
include_invalid_tool_callsNoAlso match tool calls that never ran.
conversation_initiation_sourceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.1/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds nothing on top: not that results are cursor-paginated, not that summary_mode/data_collection_ids change payload shape, not the <=100 page cap behavior.

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?

Two words is not conciseness but under-specification. For a 41-parameter listing endpoint, the description is sized far below what the task requires; nothing is front-loaded because nothing is said.

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?

This is one of the most complex list endpoints in the set (41 optional filters, pagination, response-shape toggles) with no output schema to fall back on. A two-word description leaves the agent with no notion of filtering semantics, pagination, or result shape beyond what it must reconstruct from the schema alone.

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 description coverage is 95%, so the schema itself documents nearly all 41 parameters including formats like criteria_id:result and id:op:value. With coverage this high the baseline of 3 applies; the description contributes no additional parameter meaning.

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

Purpose2/5

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

"Get Conversations" is essentially a restatement of the tool name and title, with no verb nuance, no scope statement, and no differentiation from near-identical siblings like get_conversation_history_route, get_conversation_summary_route, or list_workspace_conversation_tickets_route. It conveys only the bare resource, and only because the plural noun appears in the 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?

There is no guidance on when to use this paginated/filterable list route versus the singular get_conversation_history_route or the message-search routes (smart_search_conversation_messages_route, text_search_conversation_messages_route). No prerequisites, no exclusions, no mention that results are paginated via cursor.

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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