Search and download high-quality stock sound effects and music.
Searches for and retrieves high-quality stock music tracks based on the provided search query. Returns an array of music objects including the title, duration, audio download link, BPM, moods, and genres.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The search query string (e.g. 'dark', 'upbeat corporate'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It clearly indicates a non-destructive operation ('searches for and retrieves') and specifies the return format (array of music objects with listed fields). This provides transparent behavior for a read-only search tool, though it does not disclose edge cases like empty results or rate limits.
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?
Two sentences, front-loaded with the primary action, and each sentence serves a purpose: first describes the operation, second lists the return fields. No redundant or vague wording.
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?
For a simple one-parameter tool without an output schema, the description covers the input, purpose, and output fields comprehensively. It lacks minor details like handling of empty results or optional filters, but is complete 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.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully documents the single parameter 'query' with an example. The description only restates that the tool works 'based on the provided search query', adding no additional semantic value beyond the schema. Baseline 3 is appropriate given 100% schema coverage.
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 uses a specific verb ('searches for and retrieves') and a clear resource ('high-quality stock music tracks'), distinguishing it from the sibling tool get_sfx (sound effects). It clearly states the tool's purpose with no ambiguity.
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 implies the tool is for music (opposed to sound effects) but does not explicitly mention alternatives or when to use it over get_sfx. This is implied usage, not explicit guidance, warranting a mid-range score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Searches for and retrieves high-quality stock sound effects (SFX) based on the provided search query. Returns an array of sound effect objects including the title, duration, audio download link, BPM, moods, and genres.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The search query string (e.g. 'explosion', 'whoosh', 'footsteps'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It states the return type (an array of sound effect objects) and enumerates the fields (title, duration, download link, BPM, moods, genres), which is valuable. It does not mention pagination, result limits, or use constraints, but for a read-only search tool this is adequate transparency.
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 two sentences, front-loaded with the primary purpose, and every sentence adds value. It avoids redundancy and is appropriately sized for a simple tool.
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?
For a tool with one parameter and no output schema, the description explains the return format and fields, which is complete enough for basic usage. It lacks explicit differentiation from the sibling 'get_music,' but the name and core function make that distinction implicit. The description covers the essential context an agent needs.
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 schema description coverage is 100%, with the single 'query' parameter thoroughly described including examples. The tool description already says 'based on the provided search query,' but adds no extra semantic detail beyond the schema, so it stays at the baseline score.
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's function: searching for and retrieving stock sound effects (SFX). It uses a specific verb ('searches for and retrieves') and identifies the resource ('high-quality stock sound effects'), and the name 'get_sfx' distinguishes it from the sibling 'get_music'.
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 implies usage is for sound effect searches, but it does not explicitly mention when to use this tool over the sibling 'get_music' or provide exclusion criteria. There is no guidance on alternatives, so the context is clear but not fully specified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieves the current user's API rate limits, including requests used and remaining requests. Use this to monitor your quota.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It transparently indicates a read-only operation ('Retrieves') and specifies the exact data returned (requests used and remaining), giving the agent confidence about its side-effect-free nature. It does not disclose auth requirements or error behavior, but for a simple retrieval this is adequate.
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 composed of two sentences, each adding value. The first states the core function and output, and the second provides a practical usage hint. It is front-loaded, concise, and free of filler.
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's simplicity (no parameters, no output schema), the description fully covers the essential information: what it does, what it returns, and when to use it. There are no missing details that would hinder an agent's ability 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.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty with 100% coverage. Since there are no parameters to describe, the description doesn't need to add anything. The baseline for zero parameters is 4, and the description does not detract from it.
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's function using a specific verb ('Retrieves') and a specific resource ('the current user's API rate limits'), including the data it returns (requests used and remaining). This clearly distinguishes it from sibling tools like get_music and get_sfx, which deal with content retrieval.
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 offers explicit context for when to use the tool: 'Use this to monitor your quota.' While it does not mention when not to use it or explicitly compare with alternatives, the sibling tools are clearly in different domains, so the guidance is sufficient for a straightforward use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
get_musicget_sfxusage_statisticClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: get_music for music tracks, get_sfx for sound effects, and usage_statistic for API quota monitoring. There is no overlap or ambiguity between the tools.
Two tools follow the verb_noun pattern (get_music, get_sfx), while usage_statistic lacks a verb and uses a noun phrase. This is a minor deviation but the names remain readable and predictable.
With only 3 tools, the server is slightly minimal but well-scoped for its purpose of searching music and SFX and checking usage. Each tool serves a distinct need, so the count is appropriate but on the lean side.
The core search and retrieval workflow for music and SFX is covered, and the usage tool supports monitoring. Minor gaps exist such as no browse-by-category or direct track-by-ID retrieval, but these are not critical for the basic use case.