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assemblyai-mcp

assemblyai-mcp

by karpovantonme
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

summarize_transcript

Summarize one or more transcripts. Provide transcript IDs and optional context or answer format to get a tailored summary that fits your needs.

Instructions

Summarise one or more transcripts.

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": {
      "transcript_ids": "<transcript_ids>"
    },
    "name": "summarize_transcript"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNoLLM Gateway model. Default qwen3.5-4b-32k-fast
contextNoWhat the audio is, to steer the summary
answer_formatNoShape of the answer, e.g. bullet points
transcript_idsYesTranscripts to summarise

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to mention that this tool invokes an LLM via the gateway, depends on a configurable model, or sends transcript content to an external model — all important behavioral traits for an AI agent deciding whether the operation is appropriate.

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

Conciseness3/5

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

The description is a single sentence with no wasted words, which is concise in the literal sense. However, it is under-sized for a tool that has four parameters and no output schema, so it does not fully earn its place as the sole behavioral guide.

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

Completeness2/5

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

With no output schema and no annotations, the description should explain what the summary looks like, how multiple transcripts are combined, and what role context and answer_format play. It does none of this, leaving an agent to infer key execution details.

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?

The input schema already provides descriptions for all four parameters, so the description does not need to restate them. The phrase 'one or more transcripts' does reinforce transcript_ids having minItems=1, but it adds no deeper meaning about how model, context, or answer_format affect the result.

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

Purpose4/5

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

The description uses a specific verb ('Summarise') and a clear resource ('one or more transcripts'), making the core function immediately obvious. It does not, however, differentiate itself from the sibling ask_transcript, which could also be used to derive meaning from transcripts.

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 summarize_transcript versus ask_transcript or get_transcript. The description only states what it does, not the conditions that make it the right choice.

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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