audio_related"Find audio similar to [X]" / "more sounds like this" — related audio for a given Openverse audio ID. Use for similarity exploration in CC audio.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| results | No | Array of related audio |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "id": "a1b2c3d4-e5f6-47g8-h9i0-j1k2l3m4n5o6"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "results": {
+ "description": "Array of related audio",
+ "items": {
+ "properties": {
+ "bit_rate": {
+ "description": "Bit rate in kbps",
+ "type": "integer"
+ },
+ "category": {
+ "description": "Audio category",
+ "type": "string"
+ },
+ "creator": {
+ "description": "Audio creator name",
+ "type": "string"
+ },
+ "creator_url": {
+ "description": "Creator profile URL",
+ "type": "string"
+ },
+ "download_url": {
+ "description": "Download URL",
+ "type": "string"
+ },
+ "duration": {
+ "description": "Duration in milliseconds",
+ "type": "integer"
+ },
+ "filesize": {
+ "description": "File size in bytes",
+ "type": "integer"
+ },
+ "filetype": {
+ "description": "File format",
+ "type": "string"
+ },
+ "foreign_landing_url": {
+ "description": "Original source URL",
+ "type": "string"
+ },
+ "id": {
+ "description": "Audio unique identifier",
+ "type": "string"
+ },
+ "license": {
+ "description": "License type",
+ "type": "string"
+ },
+ "license_url": {
+ "description": "License details URL",
+ "type": "string"
+ },
+ "license_version": {
+ "description": "License version",
+ "type": "string"
+ },
+ "provider": {
+ "description": "Source provider",
+ "type": "string"
+ },
+ "sample_rate": {
+ "description": "Sample rate in Hz",
+ "type": "integer"
+ },
+ "source": {
+ "description": "Source identifier",
+ "type": "string"
+ },
+ "tags": {
+ "description": "Associated tags",
+ "items": {
+ "properties": {
+ "accuracy": {
+ "description": "Tag accuracy score",
+ "type": "number"
+ },
+ "name": {
+ "description": "Tag name",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "title": {
+ "description": "Audio title",
+ "type": "string"
+ },
+ "url": {
+ "description": "Audio URL",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool's safety profile is clear. The description adds that it returns related audio for a given ID, which is consistent but does not elaborate on behavior beyond that. Since annotations cover the main behavioral traits, a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, front-loading the command-like phrasing and use case. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has a single parameter, an output schema (which explains return values), and strong annotations, the description covers the essential purpose and parameter meaning. It is complete for a simple read-only similarity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'id' has 0% schema description coverage, but the description explains it as an 'Openverse audio ID' and the input schema includes an example. This adds necessary meaning beyond the bare schema, compensating for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds audio similar to a given Openverse audio ID, using phrases like 'Find audio similar to [X]' and 'more sounds like this'. It distinguishes from sibling tools like search_audio (keyword search) and get_audio (single retrieval) by specifying similarity exploration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use for similarity exploration in CC audio', providing clear context for when to use the tool. While it does not state when not to use it, the purpose is distinct from siblings and the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools occupy the same functional space: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions from Pipeworx data, and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. The prediction-market tools also heavily overlap in purpose, as do ai_visibility_check and scan_competitor_ai_presence. Only the Openverse media tools and memory/subscription tools are cleanly distinguishable.
All names are lowercase snake_case, but the naming conventions are mixed: verb_noun tools like search_images and resolve_entity coexist with bare verbs like remember, recall, forget, and subscribe, plus noun compounds like entity_profile, polymarket_edges, and bet_research. Subfamilies such as polymarket_* and the audio/image tools are internally consistent, but there is no single predictable pattern across the full set.
37 tools exceeds the 25+ threshold and feels inflated for the surface, especially since several could be consolidated: there are three ask_pipeworx variants and five overlapping prediction-market tools. The Openverse-specific core is only 6 tools, with 31 mostly unrelated Pipeworx and utility tools attached, making the server feel like a grab-bag rather than a purpose-built Openverse integration.
Each embedded subdomain covers its main lifecycle well: Openverse has search/get/related for images and audio, memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and research has ask, grounded, deep_research, entity_profile, compare_entities, resolve_entity, and validate_claim. Minor gaps exist—notably no Openverse video/collection tooling and no explicit memory update—but agents can work around them without hitting dead ends.