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, idempotentHint, destructiveHint. Description adds return fields and active filter context, enhancing agent understanding without contradiction.
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, front-loaded with action, no unnecessary words. Every sentence adds value.
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 no output schema, description lists return fields. With good annotations and simple tool, it is sufficiently complete for agent invocation.
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% for the single parameter. Description mentions 'active subscriptions' but the parameter include_inactive is already described in schema. No additional value beyond baseline.
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?
Clearly states 'List the caller's active subscriptions' with specific verb and resource. Distinguishes from siblings subscribe and unsubscribe by being a read-only list operation.
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?
Explicitly advises using this tool to review subscriptions before adding more or to find an id to cancel. Does not explicitly state when not to use, but context is clear.
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.
Many tools overlap in purpose: ask_pipeworx, ask_pipeworx_grounded, ask_pipeworx_beta, and deep_research all perform similar data lookups with slight variations. Prediction market tools (bet_research, polymarket_arbitrage, polymarket_edges) also overlap. Only the three PDBe-specific tools are clearly distinct, but overall the set is confusing.
Tool names follow no consistent pattern: some are verb_noun (ask_pipeworx, get_molecules), others are noun_verb (ai_visibility_check), or have mixed conventions (generate_llms_txt, uniprot_mappings). The variety of verbs (ask, bet, compare, discover, generate, get, list, recall, remember) makes it hard to predict tool names.
With 34 tools, the server is overstuffed for a single domain. It mixes PDBe-specific tools (3) with a large set of general-purpose data tools, prediction market tools, subscriptions, and memory tools. This bloat suggests the server should be split into focused services.
For the stated PDBe domain, only three tools exist (get_molecules, get_summary, uniprot_mappings), missing essential operations like search, download, or advanced queries. The server's overall purpose is unclear, and it feels like a random collection of tools rather than a coherent API.