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mshegolev/prometheus-mcp

prometheus_list_alerts

Read-onlyIdempotent

Retrieve all active and pending Prometheus alerts with labels, state, and severity counts to quickly assess system health and ongoing incidents.

Instructions

List all active and pending alerts from Prometheus.

Wraps GET /api/v1/alerts. Returns every alert that Prometheus currently tracks, with labels (including alertname, severity), state (firing / pending), the time it became active, and its current value. Also returns a summary grouped by state and a count by severity label.

Examples: - Use when: "Are there any firing alerts right now?" → check firing_count and alerts where state='firing'. - Use when: "Show me all critical alerts" → filter alerts by labels.severity == 'critical'. - Use when: Checking system health during an incident — list alerts first to understand what's firing before querying metrics. - Don't use when: You want historical alert data (Prometheus stores only current state; use Alertmanager or a recording rule for history). - Don't use when: You want raw metric values (call prometheus_query or prometheus_query_range).

Returns: dict with total_count / firing_count / pending_count / state_summary / alerts (list with labels, annotations, state, active_at, value).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
total_countYes
firing_countYes
pending_countYes
state_summaryYes
alertsYes
Behavior5/5

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

Beyond annotations (readOnlyHint, etc.), the description specifies that it returns only current state, the endpoint, and response structure (labels, state, active_at, value) with grouping by state and severity.

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

Conciseness4/5

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

Well-structured with front-loaded purpose, details, examples, and exclusions. Slightly verbose but every sentence adds value.

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

Completeness5/5

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

Comprehensive for a param-less tool with output schema. Covers purpose, usage guidance, return fields, and limitations.

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

Parameters4/5

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

No parameters exist; baseline is 4. The description adds no parameter info but uses examples to show filtering after retrieval, which is acceptable.

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?

The description clearly states it lists all active and pending alerts from Prometheus. It distinguishes itself from sibling tools (list_metrics, list_targets, query, query_range) by focusing on alerts.

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

Usage Guidelines5/5

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

Provides explicit examples of when to use (e.g., checking firing alerts, critical alerts) and when not to use (historical data or raw metric values), including alternatives like Alertmanager or prometheus_query.

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

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