get_conversation
Retrieve conversation details and full transcripts from the ElevenLabs MCP Server for analyzing completed agent interactions.
Instructions
Gets conversation with transcript. Returns: conversation details and full transcript. Use when: analyzing completed agent conversations.
Args:
conversation_id: The unique identifier of the conversation to retrieve, you can get the ids from the list_conversations tool.Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| conversation_id | Yes |
Implementation Reference
- elevenlabs_mcp/server.py:703-755 (handler)The handler function for the 'get_conversation' MCP tool. It fetches the conversation by ID using the ElevenLabs client, parses the transcript, formats details including metadata and analysis, and returns a TextContent response.
@mcp.tool( description="""Gets conversation with transcript. Returns: conversation details and full transcript. Use when: analyzing completed agent conversations. Args: conversation_id: The unique identifier of the conversation to retrieve, you can get the ids from the list_conversations tool. """ ) def get_conversation( conversation_id: str, ) -> TextContent: """Get conversation details with transcript""" try: response = client.conversational_ai.conversations.get(conversation_id) # Parse transcript using utility function transcript, _ = parse_conversation_transcript(response.transcript) response_text = f"""Conversation Details: ID: {response.conversation_id} Status: {response.status} Agent ID: {response.agent_id} Message Count: {len(response.transcript)} Transcript: {transcript}""" if response.metadata: metadata = response.metadata duration = getattr( metadata, "call_duration_secs", getattr(metadata, "duration_seconds", "N/A"), ) started_at = getattr( metadata, "start_time_unix_secs", getattr(metadata, "started_at", "N/A") ) response_text += ( f"\n\nMetadata:\nDuration: {duration} seconds\nStarted: {started_at}" ) if response.analysis: analysis_summary = getattr( response.analysis, "summary", "Analysis available but no summary" ) response_text += f"\n\nAnalysis:\n{analysis_summary}" return TextContent(type="text", text=response_text) except Exception as e: make_error(f"Failed to fetch conversation: {str(e)}") # satisfies type checker return TextContent(type="text", text="")