list_maintenance_windowsList the maintenance windows of a project across all scopes, with the window ids needed to cancel them. Set activeOnly to see just the ones in effect right now. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | No | Public ID (GUID) of the project — defaults to the project in the session context | |
| activeOnly | No | Only windows that are in effect right now |
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?
With readOnlyHint already indicating a read-only operation, the description adds useful context by stating the output includes window ids for later cancellation and that project context is required. It does not mention potential pagination or errors, but the annotation lowers the bar.
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 concise sentences: the first states the core purpose and output, the second explains the single optional parameter and a prerequisite. No redundant words or fluff.
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?
The tool is simple (list with two optional params, no output schema). The description covers what it lists, why (ids for cancellation), how to filter, and what context is needed. Nothing essential is missing for correct 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?
The schema covers both parameters with complete descriptions (projectId defaults to session context, activeOnly filters to current windows). The description only references these same semantics without adding extra detail, so baseline 3 applies.
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 'maintenance windows', and the scope 'of a project across all scopes'. It also mentions the unique output 'window ids needed to cancel them', distinguishing it from generic list tools like list_monitors or list_incidents.
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?
Provides explicit guidance on using the activeOnly parameter and notes the requirement for project context. It does not explicitly compare with alternatives, but the 'across all scopes' and 'window ids' purpose makes usage clear in context.
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 tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.
All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.
With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.
The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.