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 and destructiveHint. The description adds substantive behavioral context: it lists the exact return fields (id, type, params, created_at, last_fired_at, fire_count) and clarifies the scope ('the caller's' and 'active' by default). This goes well beyond what annotations provide.
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, then return fields, then usage context. Every word earns its place with no redundancy or fluff.
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?
Despite no output schema, the description explicitly lists all return fields, making the response shape clear. It also provides usage context and covers the tool's simple parameter set. This is complete for a list-style read 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 covers 100% of the parameter details, including a description for include_inactive. The tool description does not add any extra parameter semantics, so a baseline 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 starts with a specific verb and resource: 'List the caller's active subscriptions.' It clearly identifies what the tool does and distinguishes it from sibling tools like subscribe and unsubscribe by focusing on listing existing subscriptions.
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 gives explicit usage guidance: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This tells the agent when to use the tool and implicitly contrasts it with subscribe (adding) and unsubscribe (canceling).
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.
Several tools have heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded and validate_claim both perform claim verification, and polymarket_edges and polymarket_arbitrage both surface trading opportunities. While descriptions are detailed, the boundaries are fuzzy and agents could easily select the wrong tool.
Naming mixes verb-first (search, subscribe, recall, validate_claim) with noun-first (dataset, facets, recent, entity_profile) conventions, and some names are just adjectives or nouns. Consistent prefixed groups exist (polymarket_*, ask_pipeworx_*), but the overall style is inconsistent and the server name 'Pangaea' doesn't align with the dominant 'pipeworx' prefix.
36 tools is excessive for a coherent set, especially given the server bundles unrelated domains (earth science, general data research, prediction markets, memory, utilities). Several tools are redundant (e.g., ask_pipeworx_beta duplicates ask_pipeworx), and many are niche (ai_visibility_check, generate_llms_txt, scan_dependency) that don't fit the apparent primary purpose.
The PANGAEA dataset surface covers search, retrieval by ID/DOI, recent, and facets, but lacks export or citation tools. The Pipeworx research tools are broad, but prediction market access has no simple market-price query (only analysis-oriented tools), and there are notable gaps in lifecycle coverage for some subdomains.