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, idempotentHint=true, and destructiveHint=false, covering safety and side effects. The description adds value by specifying the exact return fields (id, type, params, created_at, last_fired_at, fire_count) and the default scope of active subscriptions. This goes beyond the annotations without contradicting them.
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?
Two sentences with no redundancy. The first sentence combines purpose and return fields; the second gives direct usage guidance. Every word 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 simple structure (one optional param, no output schema, rich annotations), the description is fully adequate. It explains what the tool returns, the default scope, and when to use it. No critical information is missing for an agent to select and correctly invoke this tool.
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 input schema has one optional parameter (include_inactive) with a description at 100% coverage. The tool description does not add any further explanation about parameters, which is acceptable since the schema already fully documents the flag. Baseline 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 starts with the specific verb 'List' and a clear resource: 'the caller's active subscriptions.' It also distinguishes this from sibling tools like 'subscribe' and 'unsubscribe' by focusing on listing rather than creating or removing. The return fields are enumerated, making the tool's function unambiguous.
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 provides usage context: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This tells the agent when to invoke this tool relative to subscribe/unsubscribe actions, making it highly actionable.
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.
Multiple tool clusters are nearly indistinguishable: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded overlap heavily (beta is explicitly identical right now), and five polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) all concern prediction-market edge detection with fuzzy boundaries. entity_profile, recent_changes, and compare_entities also blur together for company research. Only the book tools are cleanly distinct, but they are drowned by the surrounding ambiguity.
Most tools follow a consistent snake_case pattern and generally lead with a verb or clear noun (search_books, get_book, subscribe, unsubscribe, validate_claim, resolve_entity). A few depart from the verb-first convention (entity_profile, bet_research, pipeworx_trending, polymarket_edges) but the deviations are minor and do not hinder readability.
35 tools is already heavy, but the critical problem is scope: the server is named gutendex (a book API) yet only 4 of 35 tools relate to books, with the other 31 forming an unrelated Pipeworx data/research/prediction-market suite. The count is inappropriate for the advertised purpose — it feels like two or three separate servers crammed into one.
For the gutendex domain, the book tools are thin: search, get, popular, and topic browsing exist, but common Gutendex capabilities like author browsing, language filtering, sorting, and pagination controls are missing. For the actual Pipeworx suite the surface is broad, but the server's stated purpose is gutendex, and the overwhelming majority of tools are completely off-topic, creating a severe coverage mismatch.