list_platformsList all gaming platforms known to TheGamesDB (id, name, alias). Useful for resolving platform ids. Example: list_platforms({})
| Name | Required | Description | Default |
|---|---|---|---|
| _apiKey | No | Optional TheGamesDB API key. Omit to use the shared Pipeworx platform key. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {}
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds the specific returned fields (id, name, alias) but no additional behavioral traits beyond what annotations imply.
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 with no superfluous content. The example is compact and informative. Every element earns its place.
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 required parameters, no output schema), the description adequately covers purpose, return fields, and usage. It lacks mention of pagination or limits, but for a list-all tool this is acceptable.
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 description coverage is 100% (the _apiKey parameter is documented). The description does not mention the parameter, but the schema already provides the necessary meaning. Since no additional value is added, the baseline score of 3 is appropriate.
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 lists all gaming platforms from TheGamesDB and specifies the returned fields (id, name, alias). The example and mention of resolving platform IDs add clarity. It is distinct from sibling tools like get_game or search_games.
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 it is useful for resolving platform IDs, providing a clear use case. It does not explicitly state when not to use or name alternatives, but the context and sibling list make it 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.
ask_pipeworx and ask_pipeworx_beta are explicitly described as functionally identical right now, creating direct ambiguity. The six polymarket tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread, bet_research) have blurred boundaries for prediction-market tasks, and ai_visibility_check vs scan_competitor_ai_presence is a wrapper relationship. Only the memory trio and subscription lifecycle are cleanly distinct.
Naming follows multiple conventions with no global pattern: bare verbs (remember, recall, forget, subscribe), product-prefixed verbs (ask_pipeworx, pipeworx_feedback), noun phrases (entity_profile, deep_research, recent_changes), and verb_noun snake_case (discover_tools, validate_claim). There are consistent pockets (the polymarket_* family, the TheGamesDB get_/list_/search_ verbs), but the overall mix across 35 tools is inconsistent.
35 tools exceeds the 25-tool threshold for a heavy server, and the count is wildly disproportionate to the server's stated identity: only 4 of 35 tools relate to TheGamesDB while 31 belong to an unrelated Pipeworx data/prediction-market suite. The game database would justify roughly 5-10 tools, so the bulk of this surface is out of scope for the server name.
The Pipeworx portion is genuinely thorough — discovery, grounded querying, entity resolution, claim validation, subscription lifecycle, memory, and feedback form a coherent coverage. However, the namesake TheGamesDB surface is thin: search, get-by-id, list genres, and list platforms, with no games-by-platform/genre browsing, no media/screenshots beyond front boxart, and no updates feed. The set as a whole covers multiple unrelated domains with no single complete lifecycle.