trackTrack metadata by Deezer track id.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Track ID | |
| album | No | ||
| title | No | Track title | |
| artist | No | ||
| preview | No | 30-second preview URL | |
| duration | No | Duration in seconds | |
| release_date | No | Release date ISO format |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "id": 3135556
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "album": {
+ "properties": {
+ "cover": {
+ "description": "Album cover URL",
+ "type": "string"
+ },
+ "id": {
+ "description": "Album ID",
+ "type": "number"
+ },
+ "title": {
+ "description": "Album title",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "artist": {
+ "properties": {
+ "id": {
+ "description": "Artist ID",
+ "type": "number"
+ },
+ "name": {
+ "description": "Artist name",
+ "type": "string"
+ },
+ "picture": {
+ "description": "Artist image URL",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "duration": {
+ "description": "Duration in seconds",
+ "type": "number"
+ },
+ "id": {
+ "description": "Track ID",
+ "type": "number"
+ },
+ "preview": {
+ "description": "30-second preview URL",
+ "type": "string"
+ },
+ "release_date": {
+ "description": "Release date ISO format",
+ "type": "string"
+ },
+ "title": {
+ "description": "Track title",
+ "type": "string"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint: true and destructiveHint: false, so the description's minimal 'Track metadata' aligns with a read operation. However, the description adds no additional behavioral details beyond annotations, such as error handling, rate limits, or partial results. With annotations covering the basic safety profile, the description does not enhance 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 extremely concise (5 words) and front-loaded with the core action. It is not verbose, but it could benefit from a bit more structure, such as an example or context. However, for a simple lookup tool, this level of conciseness is nearly optimal.
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 that there is an output schema (not shown) and one required parameter with annotations providing safety hints, the description is minimal but sufficient for a straightforward ID-based lookup. However, it does not mention what kind of metadata is returned or any potential errors, leaving some gaps in completeness.
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 description specifies 'by Deezer track id,' which gives semantic meaning to the sole parameter 'id' beyond its type (number) and required status. It clarifies that the ID is a specific Deezer track identifier, which is crucial for correct usage. With 0% schema description coverage, this compensation is valuable.
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 states 'Track metadata by Deezer track id,' which clearly indicates the tool retrieves metadata for a specific track from Deezer. It differentiates from sibling tools like 'album' or 'artist' by specifying the entity type (track) and data source (Deezer). Slight ambiguity in verb usage but overall clear.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or when not to use it. This leaves the agent without context for selection among many similar data retrieval tools.
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.
Many tools overlap in purpose (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research all route queries to structured data), and the set mixes Deezer music tools with an unrelated Pipeworx/Polymarket suite. An agent would struggle to pick the right tool for a given request.
Naming is mixed: single-word nouns (album, artist, track, chart), verb_noun snake_case (list_subscriptions, resolve_entity), and verbose multi-concept names (scan_competitor_ai_presence, polymarket_kalshi_spread). No consistent pattern across the set.
37 tools for a server named 'Deezer' is far beyond a music API scope; the overwhelming majority are unrelated data-research, prediction-market, and utility tools. This is an extreme mismatch between the server name and the tool surface.
For the Deezer music domain, the surface is incomplete (no playlists, user library, lyrics, or radio), while the many unrelated tools each cover only fragments of their domains. The overall set lacks coherent coverage of any single purpose.