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Glama

YouTube Transcript & Search MCP Server

Batch job results

get_transcripts_results
Read-only

Read finished transcripts from a batch job, in the order submitted. Results appear as they are fetched, so this can be called before the job is done. Each entry is exactly what get_transcript returns for that video, plus its status. Page with next_page_token. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoEntries per page, 1-500 (default 100)
job_idYesid returned by submit_transcripts_job
next_page_tokenNoToken from a previous result

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
resultsNo
has_moreNo
next_page_tokenNo

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description reveals important non-blocking behavior ('Results appear as they are fetched'), the exact per-entry return shape ('exactly what get_transcript returns ... plus its status'), and cost ('Free'). It does not contradict any annotations.

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?

The description is compact with four front-loaded sentences, each carrying distinct useful information: purpose/ordering, partial-result behavior, entry format, and cost. There is no filler, making it easy for an agent to parse quickly.

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

Completeness5/5

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

For a paginated read tool with a rich output schema and readOnlyHint, the description covers order, partial results, content shape, cost, pagination, and the timing. Nothing essential for correct invocation is missing.

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?

Since the input schema already provides 100% description coverage for all three parameters, the description does not need to add parameter details. It only mentions next_page_token in a pagination example, adding no meaning beyond the schema.

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 ('Read') and a clear resource ('finished transcripts from a batch job') plus ordering ('in the order submitted'), making the primary purpose unambiguous. However, it does not explicitly differentiate itself from the similarly named sibling get_transcripts_result, which could confuse an agent choosing between the two.

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?

The description gives clear usage context: it can be called before the job completes and pagination is done with next_page_token. It does not mention any alternatives or when not to use the tool, so it falls short of explicit when/when-not guidance.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools target a distinct resource and action: search, list, metadata, transcript, job lifecycle, and credits. The get_transcripts_job / get_transcripts_result / get_transcripts_results trio is easy to blur at first glance, but the descriptions clearly differentiate job status, one result, and paged results.

Naming Consistency4/5

The set mostly follows a predictable verb_noun pattern: get_, list_, search_, submit_, cancel_. The main deviation is latest_channel_videos, which uses an adjective instead of a verb, and the result/results pair is mildly confusing, but overall naming is coherent and easy to navigate.

Tool Count5/5

14 tools is well within the sweet spot for a server with this scope. Each tool serves a clear niche: video lookup, metadata, single transcripts, batch jobs, and search are all represented without unnecessary or redundant tools.

Completeness5/5

The server provides full coverage of the transcript and search workflow: search YouTube, list channel/playlist videos, fetch or batch-fetch transcripts, check job progress/credits, and read results. There are no obvious missing operations that would force an agent into a dead end.