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sandraschi

Observability MCP Server

manage_alert_configs

Manage metric alert configurations by listing, adding, removing, or toggling alerts to control active monitoring and keep alerting aligned with current needs.

Instructions

Manage metric alert configurations.

Operations:

  • list: List all current alert configurations

  • add: Add a new alert configuration (requires 'alert' dict)

  • remove: Remove an alert by metric name (requires 'metric_name')

  • toggle: Enable/disable an alert (requires 'metric_name')

Input Schema

NameRequiredDescriptionDefault
alertNo
operationYes
metric_nameNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure for a state-mutating tool. It never states whether add/remove/toggle take effect immediately, whether removal is reversible, what permissions are needed, or what happens if the metric name doesn't exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded one-line purpose followed by a compact operation list; every line conveys either an action or a precondition, with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need not be described, and the operation enumeration covers the call surface. Still, with zero annotations on a mutation tool and an unspecified 'alert' payload schema, an agent cannot confidently construct a valid 'add' call or predict side effects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does important compensating work by defining the legal values of 'operation' (the schema has no enum) and tying 'metric_name'/'alert' to specific operations. But the 'alert' dict — an open additionalProperties object — is left entirely opaque, which is the most consequential parameter for 'add'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Manage metric alert configurations') and then enumerates the four supported operations, which makes it clearly distinguishable from siblings like alert_on_anomalies (event alerting) and the dashboard/datasource management tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The operation list with per-operation requirements ('add' requires 'alert' dict, 'remove'/'toggle' require 'metric_name') tells the agent which operation to pick and what it needs. However, there is no explicit when-to-use-vs-alternatives guidance and no mention of how this differs from alert_on_anomalies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.