Podcast Index MCP

Random episodes

get_random_episodes

Read-only

Pull random podcast episodes to sample the real contents of a category, with optional filters for language and category. Every call returns a different set.

Instructions

Random episodes from across the index, optionally filtered by language and category. Genuinely random rather than ranked, which makes it useful for sampling what a category actually contains rather than what its top shows look like. Never cached, so calling it again gives different episodes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_random_episodes"
  }
}

Input Schema

Name	Required	Description
`cat`	No	Categories to include, by name or id, comma-separated.
`max`	No	How many to return. Defaults to 10.
`lang`	No	Language code such as en, es, de. Comma-separate several.
`notcat`	No	Categories to exclude, by name or id, comma-separated.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 1, 2026

TDQS

A4.4/5.0

Behavior5/5

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

The description adds meaningful behavioral detail beyond the annotations: results are genuinely random, never cached, and repeated calls yield different episodes. This complements the readOnlyHint and idempotentHint=false annotations without contradicting them.

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?

Three sentences, each earning its place: the first defines the operation, the second explains why it is useful, and the third discloses a non-obvious behavior. The most important information is front-loaded.

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?

For a read-only tool with four optional parameters and complete schema documentation, the description is sufficient to select and invoke it correctly. It explains the random behavior and the sampling use case, though it does not describe the response shape, which is acceptable given no output schema is provided.

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 description coverage is 100%, so the parameters are already well documented. The description adds conceptual context around language and category filtering, but does not provide additional syntax, defaults, or format details beyond what the schema already gives.

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 clearly states a specific action and resource: retrieving random episodes from across the whole index with optional filters. It explicitly contrasts with ranked results, which helps distinguish it from tools like get_trending and get_recent_episodes even without reading their schemas.

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 a clear use case: sampling what a category actually contains rather than what popular shows look like. It implies when to choose this tool over ranked or recent alternatives, though it does not name specific sibling tools or state explicit when-not-to-use conditions.

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