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, so the safety profile is covered. The description adds useful context beyond annotations, such as returning specific fields (id, type, params, created_at, last_fired_at, fire_count) and the scope ("caller's"), which helps the agent understand what to expect from the response.
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 only two sentences, front-loaded with the core action, and every clause earns its place. It lists return fields and gives practical usage guidance without any fluff or repetition.
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?
This is a simple read-only list tool with one optional parameter and no output schema. The description covers the return fields, which is essential because there is no output schema, and provides usage context. It does not mention the include_inactive parameter, but the schema already fully documents that, so the description is sufficiently complete for the tool's simplicity.
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 only parameter, include_inactive, is fully documented in the input schema with a clear description and default behavior. The tool description does not add any parameter-specific details, but with 100% schema coverage, a baseline score 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 distinguishes this from sibling tools like subscribe and unsubscribe, and enumerates the exact return fields, making the tool's purpose 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 states when to use the tool: "Use this to review what you're monitoring before adding more or to find an id to cancel." This gives clear situational guidance, though it does not name alternative tools (e.g., subscribe/unsubscribe) by name, stopping short of a full 5.
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.
The set has several overlapping tool clusters. ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior, ai_visibility_check and scan_competitor_ai_presence overlap heavily, and polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, and polymarket_fill_risk all target opportunity-finding/fill-checking on prediction markets. While individual descriptions are detailed, an agent could easily pick the wrong tool among these near-duplicates.
Naming is inconsistent across the surface. The monday_* and polymarket_* prefixes are consistent within their subgroups, and ask_pipeworx_* forms a family, but the rest mix verb_phrase (validate_claim, compare_entities, discover_tools), noun_phrase (entity_profile, recent_changes, suggest_questions), and bare verbs (remember, forget, recall) with no unifying pattern. This makes it hard to predict tool names.
At 36 tools, the surface is overloaded. The Monday.com integration alone only needs 5 tools, and the remaining 31 are a sprawling research/meta-toolkit. Many of these could be consolidated (e.g., ask_pipeworx and ask_pipeworx_beta, or the several polymarket scanners), so the count feels inflated beyond what the server's core purpose requires.
The data-research and monitoring side is thorough, covering querying, grounding, comparison, profiling, entity resolution, subscriptions, memory, and feedback. However, the Monday.com integration is incomplete: it offers create/list/get/search for items but no update or delete operations, and no board creation or modification. This leaves the Monday workflow with dead ends.