Skip to main content
Glama

Search your library, including transcripts

search_library
Read-onlyIdempotent

Search all podcast episodes in your library by keyword; results show whether matches came from titles, notes, or transcripts, helping you find the episode that discussed a topic or only mentioned it.

Instructions

Keyword search across every episode of every show in your library: titles, show notes, and the transcript excerpts Apple has cached. This is the closest thing to full-text search over everything you follow, and it answers 'which episode was that in'. Each result says whether the term matched the title, the notes, or the transcript, which matters: a title match means the episode is about the term, a transcript-only match means someone mentioned it in passing. The excerpts are excerpts, not full transcripts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullNoReturn complete notes and excerpts instead of trimmed ones. Much larger.
showNoRestrict to one show, by local id, Apple id, or title. Omit to search everything.
limitNoHow many to return, 1-200. Episodes to return, newest first.
queryYesThe word or phrase to look for. Matching is literal, not fuzzy.
include_transcriptsNoSearch the cached transcript excerpts as well as titles and notes. On by default, and it is the point of this tool.
Install Server

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds useful behavioral details: results distinguish title, notes, or transcript matches, and the transcript results are excerpts, not full transcripts. This helps set expectations about coverage and interpretation of results.

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 four focused sentences that all add value: it states the scope, explains the intended use case, clarifies what match types mean, and warns about excerpt limitations. It is front-loaded and lacks fluff.

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

Completeness4/5

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

The schema covers all parameters and the annotations cover safety characteristics. The description covers the key behavioral expectations, such as match-type reporting and excerpt-only transcripts. Without an output schema, it could specify the exact response structure a bit more, but it gives enough for an agent to select and invoke the tool correctly.

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 covers 100% of parameters with descriptions, so the baseline is 3. The description does not discuss parameters directly, but it does add context about transcript excerpts being cached and partial, which is relevant to understanding the results. No additional parameter semantics are needed.

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?

The description states a spécific verb ressource and scope: keyword search across every episode and show in the library, including titles, show notes, and transcript excerpts. It clearly answers the user's typical query, 'which episode was that in', and its emphasis on library-wide transcript search differentiates it from sibling search tools.

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 context for when to use the tool: when the user wants full-text search over everything they follow and needs to locate an episode by keyword. It does not explicitly name alternatives or state when not to use it, but the intended usage is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/navidmoazzez/apple-podcasts-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server