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 provide readOnly, idempotent, non-destructive hints. Description adds return fields but no new behavioral context beyond what annotations convey.
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 purpose and return fields, no wasted words.
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 strong annotations, the description adequately covers return fields and usage context. No output schema but sufficient for task.
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% and describes the boolean parameter. Description mentions 'active subscriptions' implying default behavior, but adds little beyond schema's parameter description.
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 it lists the caller's active subscriptions, specifies return fields (id, type, etc.), and distinguishes from sibling tools like subscribe/unsubscribe.
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 says 'use this to review what you're monitoring before adding more or to find an id to cancel', providing context for when to use it, though it does not name alternative tools explicitly.
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 or explicitly duplicate purposes: ask_pipeworx_beta is described as currently identical to ask_pipeworx, while ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim all route natural-language queries to similar lookup pipelines. The Polymarket tools also blur together (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk), and scan_competitor_ai_presence is just a wrapper around ai_visibility_check.
There are readable verb-led names like search_publications, get_project, resolve_entity, and validate_claim, but the set mixes conventions with noun-phrase names like entity_profile, recent_alerts, polymarket_edges, and pipeworx_trending. The lack of a single verb_noun pattern makes the surface feel inconsistent, though each family is internally recognizable.
At 37 tools, this is well beyond the 25+ threshold where an agent starts paying significant selection and context cost. The broad domain could justify some breadth, but many tools are meta-wrappers or near-duplicates (ask_pipeworx_beta, compare_entities, entity_profile, deep_research) that inflate the count.
Within its main subdomains, the surface is fairly complete: OpenAIRE search has matching get_project/get_research_product retrieval, memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and there are discovery/onboarding helpers like suggest_questions and discover_tools. Minor gaps exist (e.g., no direct generic Polymarket market quote tool, no memory update besides overwrite), but no major workflow is a dead end.