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assemblyai-mcp

assemblyai-mcp

by karpovantonme
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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search_transcript

Find where specific words appear in a transcript. Get match counts and timestamps to locate spoken terms quickly.

Instructions

Find where words are spoken in a transcript. Returns counts and timestamps.

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_id": "<transcript_id>",
      "words": "<words>"
    },
    "name": "search_transcript"
  }
}

Input Schema

NameRequiredDescriptionDefault
wordsYesWords to look for. Timestamps come back per match
transcript_idYesId of a completed transcript

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It doe disclose that the tool returns counts and timestamps, but it does not describe matching semantics, result structure, or any edge cases. This is basic but adequate transparency with clear gaps.

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?

Two short sentences with no filler. The verb-resource statement is front-loaded and the output expectation follows directly. Every word earns its place.

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

Completeness3/5

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

For a simple two-parameter tool with no output schema, the description gives enough to attempt an invocation, but it leaves return-format details and search behavior unspecified. It is complete at a high level, yet lacks precision an agent might want before calling.

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 100%, so the schema already documents both transcript_id and words. The description adds no parameter-level detail beyond what the schema provides, so the baseline 3 is appropriate.

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?

States a specific verb and resource: 'Find where words are spoken in a transcript.' It also names the output ('counts and timestamps'), which clearly distinguishes it from sibling tools like get_transcript, get_speaker_turns, or ask_transcript.

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

Usage Guidelines4/5

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

Clear context for when to use it: whenever an agent needs to locate where particular words occur in a transcript and get counts/timestamps. It does not explicitly list exclusions or alternatives, so it misses the full 5, but the intended use is directly inferable.

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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