get_labelFetch a Discogs record label profile by label_id. Returns label name, profile, contact info, URLs, parent label, sublabels, and images.
| Name | Required | Description | Default |
|---|---|---|---|
| label_id | Yes | Discogs label ID |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "label_id": 1
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Label profile information from Discogs API",
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, etc. Description adds detail on return fields and confirms read-only nature. No contradictions.
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?
One concise sentence that front-loads the purpose and lists return values. No superfluous content.
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 simple parameter and existence of output schema, the description adequately covers the tool's behavior and return value composition.
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?
Schema coverage is 100% with a description for label_id. The tool description does not add additional meaning beyond the schema, meeting the baseline.
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?
Clearly states it fetches a Discogs record label profile by label_id and lists returned fields (name, profile, contact info, URLs, etc.). Distinguishes from siblings like get_artist, get_master, get_release.
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?
Does not explicitly state when to use this tool over alternatives or provide exclusions. Usage is implied from the resource type, but no direct guidance.
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.
There is severe overlap among tools: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants, and deep_research, discover_tools, and suggest_questions all serve discovery/research purposes. The Discogs-specific tools are distinct, but the large number of redundant Pipeworx tools makes it impossible to tell which one to pick.
The Discogs tools follow a clean verb_noun pattern (get_artist, get_label, get_master, get_release), but the majority of the set uses inconsistent, domain-specific names (deep_research, generate_llms_txt, polymarket_arbitrage, scan_competitor_ai_presence). No single naming convention is applied across the server.
With 36 tools, the server is massively over-provisioned for a Discogs-focused API. Most tools (e.g., ask_pipeworx, polymarket_edges, SEC lookups) have nothing to do with Discogs and belong to a separate service. The Discogs surface alone could be served by ~6 tools (search, get_artist, get_label, get_master, get_release, search_within), so the count is wildly inappropriate.
For the Discogs domain, the core entities (artist, label, master, release) and full-text search are present, plus semantic search inside records. However, there are gaps like user collections, wantlists, marketplace, and discogs-specific filters beyond format/country. The presence of many unrelated tools does not directly hurt domain coverage, but the Discogs surface is not exhaustive.