wishlistdoc-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| audit_steam_storeA | Audit a Steam game store page health score (0-100), letter grade (S/A/B/C/D/F), 6 algorithmic dimensions (tags, localization, pricing resistance, demo loop, visual assets, short description), and prioritized actionable prescriptions. Powered by WishlistDoc (https://wishlistdoc.com). |
| predict_sales_coneA | Forecast Steam first-week unit sales and first-year gross revenue across P10 (pessimistic floor), P50 (median benchmark), and P90 (breakout ceiling) confidence tiers. Powered by WishlistDoc empirical game discovery models. |
| get_genre_benchmarksA | Retrieve Steam industry launch conversion benchmarks, Year-1 revenue multipliers, and 270-day wishlist decay curves for specific game genres (RPG, Action, Simulation, Horror, Casual, or all). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool targets a distinct domain: store page audit, sales forecasting, and genre benchmarks. There is no overlap in purpose or output.
All tool names use a consistent verb_noun pattern (audit_steam_store, predict_sales_cone, get_genre_benchmarks). Minor deviation: 'sales_cone' is a domain-specific term while the others are generic, but the pattern is consistent.
Three tools is on the lower end but appropriate for a focused niche server covering audit, prediction, and benchmarks. It feels slightly thin but each tool is substantial and distinct.
The server covers core wishlist/sales analysis workflows, but lacks obvious related operations like fetching wishlist counts, comparing games, or updating/refreshing audits. Agents can work around gaps but the surface is minimal.