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 readOnly, idempotent, and non-destructive hints. The description adds that it returns specific fields and implies only active subscriptions by default, but no additional behavioral traits beyond 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 concise sentences with no redundant information, front-loading the purpose and usage.
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 lists returned fields. Usage guidance and parameter are well-documented. Sibling tools provide context. The definition is complete for this simple read-only 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 the single parameter 'include_inactive' with a description, achieving 100% coverage. The tool description does not add extra meaning, so 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 clearly states the verb 'list', the resource 'subscriptions', and specifies scope 'caller's active'. It also lists returned fields, distinguishing it from siblings like subscribe and 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?
The description provides explicit use cases: 'review what you're monitoring before adding more' and 'find an id to cancel'. It does not mention when not to use or alternatives, but the context is adequate.
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 have overlapping purposes, e.g., ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile, and compare_entities all retrieve factual data about entities. Additionally, multiple polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) are highly specialized but can be confused without careful reading of descriptions.
Naming conventions are highly inconsistent: snake_case (ai_visibility_check, generate_llms_txt), lowercase phrases (ask_pipeworx, forget, recall), and mixed styles (entity_profile, scan_competitor_ai_presence). No clear pattern like verb_noun; tools like 'remember' and 'forget' are single words while others are lengthy phrases.
32 tools is on the high side for a single server, but the coverage is broad (data retrieval, prediction markets, Finnish registry, memory, utilities). However, many tools are redundant or overly specialized, making the count feel bloated. A more focused set could be 20-25 tools.
The Pipeworx tools provide deep coverage for factual data retrieval, and the Finnish registry has basic operations. However, there are gaps in other areas, and the set lacks a unified domain. The inclusion of memory tools and a random llms.txt generator feels out of place, breaking the coherence.