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, and destructiveHint as safe. The description adds value by specifying the exact fields returned (id, type, params, created_at, last_fired_at, fire_count), providing detail beyond the 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 extremely concise—two sentences with no extraneous information. It is front-loaded with the core purpose and immediately useful.
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 listing tool with one optional parameter and no output schema, the description fully covers purpose, return format, and usage context. No information is missing.
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 has 100% coverage with one optional boolean parameter 'include_inactive' described in the schema. The tool description does not add any extra semantics beyond the schema, 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 clearly states 'List the caller's active subscriptions' and lists the returned fields (id, type, params, etc.). It distinguishes itself from sibling tools like 'subscribe' and 'unsubscribe' by being the listing tool.
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.' It provides context on when to use the tool, though it does not explicitly state when not to use it.
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 overlapping or duplicate roles: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and deep_research/ask_pipeworx/discover_tools/suggest_questions all serve query routing. The five ENTSO-E tools are distinct but are lost among the unrelated Pipeworx/prediction-market tooling.
Naming mixes single verbs (remember, forget, subscribe), noun phrases (actual_load, entity_profile), verb_noun patterns (compare_entities, discover_tools), and brand-prefixed groups (pipeworx_*, polymarket_*). Snake_case is consistent, but the verb style and naming logic vary widely with no discernible overall pattern.
36 tools is too many for a server supposedly focused on ENTSO-E electricity data, especially since only 5 tools serve that domain. Even as a general data-access server, the set is heavy and includes redundant/beta variants (ask_pipeworx_beta, ask_pipeworx_grounded) that inflate the count.
The server name 'Entso E' implies electricity-market data, but only 5 of 36 tools cover generation, load, prices, capacity, and cross-border flow. Missing typical ENTSO-E operations like forecasts, balancing, or real-time grid status, while the remaining 31 tools belong to an unrelated data platform — severely incomplete for the advertised purpose.