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mshegolev/prometheus-mcp

correlate_alerts_across_instances

Read-onlyIdempotent

Correlate alerts across multiple Prometheus instances using temporal windows and label similarity to identify related incidents and systemic issues.

Instructions

Correlate alerts across multiple Prometheus instances.

Identifies related alerts that fire simultaneously or in sequence across different Prometheus instances using temporal windows and label similarity.

Use this to:

  • Understand cross-instance incident scope

  • Identify related alerts in different clusters/regions

  • Detect systemic issues affecting multiple instances

Examples: - "Are there related alerts firing across our US and EU clusters?" - "Show me alerts that might be related to this HighCPU alert"

Returns: CorrelationResult with correlated alerts, groups, and cascades.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instanceNo
instancesNo
enable_rcaNoEnable root cause analysis enhancement (default: False)
temporal_windowNoTime window in seconds for correlation (default: 300)
similarity_thresholdNoMinimum similarity score for correlation (default: 0.7)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupsYes
cascadesYes
rca_enhancementYes
correlated_alertsYes
total_correlationsYes
instance_attributionYes
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds value by explaining the method (temporal windows and label similarity) and what is returned (CorrelationResult with groups and cascades). No contradictions or hidden side effects are mentioned.

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?

The description is well-structured: a one-line summary, method explanation, bulleted use cases, examples, and return value specification. No unnecessary sentences; every part adds value.

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

Completeness4/5

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

Given the tool's complexity (5 parameters, cross-instance correlation) and the presence of an output schema, the description covers purpose, usage, and method well. However, it fails to explain the distinction between the 'instance' and 'instances' parameters, which is important for correct invocation. Overall, still fairly complete.

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 descriptions cover 3 of 5 parameters (enable_rca, temporal_window, similarity_threshold) adequately. However, the two pivotal parameters 'instance' and 'instances' lack descriptions, and the description does not clarify their relationship (e.g., single vs list, mutual exclusivity). This is a gap that could lead to incorrect usage.

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 'Correlate alerts across multiple Prometheus instances'. It uses a specific verb (correlate) and resource (alerts across instances), and distinguishes itself from siblings like detect_cascading_alerts which likely operates within a single instance.

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 description provides explicit use cases: understanding cross-instance incident scope, identifying related alerts in different clusters/regions, detecting systemic issues. It also gives example queries. However, it does not explicitly mention when not to use or directly point to alternatives, though the context of siblings implies differentiation.

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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