List all monitors in the authenticated LastPing project. Returns id, name, slug, status, ping_url for each. Use the tag param to filter by a single tag.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Optional tag to filter by, e.g. 'agent:claude'. Returns only monitors that have this tag. |
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?
The description describes a non-destructive read/list operation, but annotations declare readOnlyHint=false, idempotentHint=false, and destructiveHint=true. This is a direct contradiction: an agent could wrongly believe calling this tool may destroy resources. The description provides no mitigating behavioral context.
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 tight sentences, front-loads the core action and output fields, and adds the filter instruction without unnecessary detail. Every sentence earns its place.
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 description provides return fields and project authentication context, which is useful given there is no output schema. However, the annotation contradiction leaves the tool's behavioral profile ambiguous and potentially misleading, so the description is not fully contextually complete.
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 already fully documents the single 'tag' parameter with syntax, example, and filtering semantics. The description only repeats that information, so it adds no meaningful value beyond the schema. Baseline 3 applies due to 100% schema coverage.
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 uses a specific verb and resource ('List all monitors') and states exactly what is returned (id, name, slug, status, ping_url). This clearly distinguishes it from get_monitor, pause_monitor, resume_monitor, and other monitor-related siblings.
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 identifies the authenticated project scope and explains the optional tag filter with an example. It does not explicitly contrast with alternatives such as get_monitor, but the list-vs-single distinction is implicit and clear enough.
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.
Tools are organized by clear resource domains, and the long descriptions carefully separate similar reads. The main ambiguity is create_monitor's upsert behavior overlapping with update_monitor, and list_incidents vs list_open_incidents could be confused from names alone.
Almost every tool uses verb_noun snake_case with a consistent CRUD vocabulary like create_, list_, get_, update_, and delete_. Minor deviations exist: get_alert_templates is really a list operation, and discover_monitors_reconcile is an awkward verb-object-verb construction.
Thirty-six tools is a heavy surface for an agent to navigate, even for a full monitoring platform. Most tools are individually purposeful, but the count exceeds the range where an agent can quickly scan and select, and the set would be easier to handle if split across domains.
Coverage is strong: monitors, destinations, agents, status pages, API keys, routes, alert templates, incidents, run history, discovery, and Terraform export all have read and lifecycle operations. Minor gaps remain, such as no explicit single-incident view and no acknowledgment/resolution action beyond notes, but core workflows have no dead ends.
