list_subscriptionsList the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
| Name | Required | Description | Default |
|---|---|---|---|
| include_inactive | No | Include cancelled subscriptions in the response (default false). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's a safe read. The description adds value by disclosing the default behavior (active only) and the returned fields (id, type, params, timestamps, fire_count), which goes beyond the annotations.
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 action, and includes both return fields and usage guidance. Every sentence earns its place with no redundancy.
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 list tool with one optional parameter and no output schema, the description is complete: it states the purpose, default behavior, returned fields, and practical use cases. No critical information appears missing.
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 the single parameter 'include_inactive' fully described. The description does not add additional parameter semantics beyond what the schema provides, so 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 'List the caller's active subscriptions' with a specific verb and resource. It differentiates from sibling tools like subscribe and unsubscribe by focusing on listing, and the return fields are specified.
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 provides explicit use cases: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This gives clear context for when to use the tool, though it does not explicitly mention alternatives or exclusions.
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 currently described as functionally identical, creating a clear misselection risk, and several query/answer tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim, entity_profile, compare_entities) have overlapping boundaries. The Polymarket tools also blur into each other, so despite verbose descriptions, an agent can easily route a request to the wrong tool.
All names are snake_case and readable, but the conventions are mixed: verb_noun (ask_pipeworx, resolve_entity), noun_noun (entity_profile, bet_research), bare verbs (remember, recall, forget, profile), and prefix families with inconsistent ordering (ask_pipeworx vs pipeworx_feedback, polymarket_edges vs polymarket_kalshi_spread). This is not chaotic, but there is no single predictable naming pattern.
36 tools is well past the 25+ threshold for a heavy surface, and the server name 'Mojang' implies a narrow Minecraft API scope while only 5 tools relate to Minecraft. The rest belong to a broad data-research, prediction-market, and memory platform, making the tool count feel inflated and mis-scoped for the server's stated identity.
For the implied Minecraft/Mojang domain, there are obvious gaps such as no authentication, skin/name mutation, or broader account endpoints, so that surface is thin. Meanwhile, the Pipeworx data side is fairly complete, but because two unrelated domains are jammed into one server, neither domain is covered in a coherent, trustworthy way.