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ask_attention is the workhorse of multi-call analysis. Instead of fetching each transcript and asking the LLM to reason over them, hand a list of call IDs (or a deal ID) plus a prompt to Attention’s analysis engine — it processes all the calls server-side and returns a focused answer. This is dramatically more efficient than calling get_call_details in a loop.

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Tools

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ask_attention

Scope: mcp:read.
Analyze calls by running AI analysis across up to 25 calls in a single request. Provide either a list of call IDs (typically returned from search_calls) or a deal ID — the engine pulls all conversations associated with that deal automatically.
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prompt
string
required
The question or analysis prompt to run against the calls. Be specific about what to surface (objections, pricing mentions, next steps, etc).
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conversation_ids
array
List of call IDs to analyze. Provide this or deal_id.
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deal_id
string
Deal ID to analyze all associated calls. Provide this or conversation_ids.
Returns: A Markdown answer to the prompt, grounded in the supplied calls. Includes references back to specific calls when relevant. Example prompt: “Across these 12 calls with Datadog, what are the recurring objections and how have they evolved over the deal’s lifetime?”
The recommended pattern is search_calls → ask_attention rather than fetching each transcript with get_call_details. The engine reads transcripts, scorecard results, and intelligence items in a single pass.