Podcast Index MCP

Trending podcasts

get_trending

Read-only

Find popular podcasts by category and language using Podcast Index's own trend signal. Filter by category, language, and time window to see what's hot right now or over a longer period.

Instructions

Shows trending in the index right now, which is Podcast Index's own popularity signal rather than a chronological list. This is the tool for 'what is hot in this category'. Filter by category and language to make it useful: unfiltered, it returns whatever is big across all of podcasting, which is rarely the question. The window defaults to the last few days; widen it with 'since' for a slower, more stable read.

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_trending"
  }
}

Input Schema

Name	Required	Description
`cat`	No	Categories to include, by name or id, comma-separated. Call list_categories for the names.
`max`	No	How many to return. Defaults to 20.
`lang`	No	Language code such as en, es, de. Comma-separate several.
`since`	No	Only include things published after this time, as a unix timestamp in seconds. A negative number is read as seconds before now, so -604800 means the last week.
`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

A4.9/5.0

Behavior5/5

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

Annotations already cover read-only and non-destructive safety. The description adds meaningful behavior beyond annotations: it explains the semantics of the trending signal, the default time window, and how 'since' changes the read. This context is not available from annotations alone and helps the agent calibrate expectations.

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 three tight sentences with clear structure: purpose first, then usage context, then parameter guidance. Every sentence earns its place, and nothing is redundant or verbose.

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?

With a low-complexity tool, rich annotations, and a fully documented schema, the description provides the essential conceptual context that schema cannot: what 'trending' means, when to use it, and how to adjust parameters. No output schema is required to explain return values, and the description is sufficient for an agent to solicit and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds usage-specific value by recommending filters (category, language) and explaining how 'since' widens the window for a slower, more stable read, which goes beyond the schema's raw descriptions. It does not cover every param, but the schema already does.

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 ('Shows') and resource ('trending in the index'), and clarifies it is a popularity signal rather than a chronological list. It distinguishes the tool from chronological list endpoints like get_recent_episodes and positions it for the 'what is hot in this category' use case.

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

Usage Guidelines5/5

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

Explicitly declares when to use the tool: 'This is the tool for "what is hot in this category". It also gives when-not by noting it is 'rather than a chronological list', and provides actionable filter advice (category/language, widen 'since') for a better read.

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