list_status_pagesList public/private status pages with company name, subdomain, aggregate_state, and published flag. Uptime API: GET /api/v2/status-pages.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number for pagination (default 1). | |
| per_page | No | Results per page. | |
| team_name | No | Filter by team name (only when using a global API token). |
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 declare read-only, which matches. Description adds context by naming returned fields and the API endpoint, providing value beyond annotations. No contradictions.
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: one functional description and one API reference. No redundancy or unnecessary words. Highly efficient.
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?
Describes returned fields and mentions pagination parameters. Without an output schema, this is helpful. Could mention response structure (e.g., array of objects) for completeness, but adequate.
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 covers all parameters with descriptions (100% coverage). Description adds meaning by listing the output fields (company name, subdomain, etc.), which the schema does not specify due to missing output schema.
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 status pages with specific fields and the API endpoint. Distinguishes from sibling tools which manage different resources.
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?
No explicit guidance on when to use vs. alternatives. While contextually clear due to different resource types, the description lacks explicit 'when-to-use' or 'when-not-to-use' information.
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.
Each tool targets a distinct resource or action: monitors, heartbeats, incidents, on-call schedules, and status pages are clearly separated. Incident actions (list, get, acknowledge, resolve) are unambiguous with no overlap.
All tools follow a consistent verb_noun pattern in snake_case (e.g., list_monitors, get_incident, acknowledge_incident). The naming is predictable and easy to follow.
With 9 tools covering the primary aspects of uptime monitoring and incident management, the count is well within the ideal 3-15 range. Each tool serves a clear purpose without being excessive.
The tool set covers reading and incident lifecycle management well, but lacks any create/update/delete operations for monitors, heartbeats, or status pages. This is a notable gap for a comprehensive monitoring platform, though the core incident workflow is covered.