prometheus-mcp

A Model Context Protocol (MCP) server for Prometheus integration. Give your AI assistant eyes on your metrics and alerts.

Status: Planning Author: Claude (claude@arktechnwa.com) + Meldrey License: MIT Organization: ArktechNWA

Why?

Your AI assistant can analyze code, but it can't see if your services are healthy. It can suggest optimizations, but can't see the actual latency metrics. It's blind to the alerts firing at 3am.

prometheus-mcp connects Claude to your Prometheus server — read-only, safe, insightful.

Philosophy

1. Read-only by design — Prometheus queries don't mutate state
2. Query safety — Timeout expensive queries, limit cardinality
3. Never hang — PromQL can be expensive, always timeout
4. Structured output — Metrics + human summaries
5. Fallback AI — Haiku for anomaly detection and query help

Features

Perception (Read)

• Instant queries (current values)
• Range queries (over time)
• Alert status and history
• Target health
• Recording rules and alerts
• Label discovery
• Metric metadata

Analysis (AI-Assisted)

• "Is this metric normal?"
• "What caused this spike?"
• "Suggest a query for X"
• Anomaly detection

Permission Model

Prometheus is inherently read-only for queries. Permissions focus on:

Query Safety

{
  "query_limits": {
    "max_duration": "30s",
    "max_resolution": "10000",
    "max_series": 1000,
    "blocked_metrics": [
      "__.*",
      "secret_.*"
    ]
  }
}

Safety features:

• Query timeout enforcement
• Cardinality limits
• Metric blacklist patterns
• Rate limiting

Authentication

{
  "prometheus": {
    "url": "http://localhost:9090",
    "auth": {
      "type": "none" | "basic" | "bearer",
      "username_env": "PROM_USER",
      "password_env": "PROM_PASS",
      "token_env": "PROM_TOKEN"
    }
  }
}

Tools

Queries

prom_query

Execute instant query (current values).

prom_query({
  query: string,            // PromQL expression
  time?: string             // evaluation time (default: now)
})

Returns:

{
  "query": "up{job=\"api\"}",
  "result_type": "vector",
  "results": [
    {
      "metric": {"job": "api", "instance": "api-1:8080"},
      "value": 1,
      "timestamp": "2025-12-29T10:30:00Z"
    }
  ],
  "summary": "3 of 3 api instances are up"
}

prom_query_range

Execute range query (over time).

prom_query_range({
  query: string,
  start: string,            // ISO timestamp or relative: "-1h"
  end?: string,             // default: now
  step?: string             // resolution: "15s", "1m", "5m"
})

Returns:

{
  "query": "rate(http_requests_total[5m])",
  "result_type": "matrix",
  "results": [
    {
      "metric": {"handler": "/api/users"},
      "values": [[1735470600, "123.45"], ...],
      "stats": {
        "min": 100.2,
        "max": 456.7,
        "avg": 234.5,
        "current": 345.6
      }
    }
  ],
  "summary": "Request rate ranged from 100-457 req/s over the last hour, currently 346 req/s"
}

prom_series

Find series matching label selectors.

prom_series({
  match: string[],          // label matchers
  start?: string,
  end?: string,
  limit?: number
})

prom_labels

Get label names or values.

prom_labels({
  label?: string,           // get values for this label (omit for label names)
  match?: string[],         // filter by series
  limit?: number
})

Alerts

prom_alerts

Get current alert status.

prom_alerts({
  state?: "firing" | "pending" | "inactive",
  filter?: string           // alert name pattern
})

Returns:

{
  "alerts": [
    {
      "name": "HighErrorRate",
      "state": "firing",
      "severity": "critical",
      "summary": "Error rate > 5% for api service",
      "started_at": "2025-12-29T10:15:00Z",
      "duration": "15m",
      "labels": {"job": "api", "severity": "critical"},
      "annotations": {"summary": "..."}
    }
  ],
  "summary": "1 critical, 0 warning alerts firing"
}

prom_rules

Get alerting and recording rules.

prom_rules({
  type?: "alert" | "record",
  filter?: string
})

Targets

prom_targets

Get scrape target health.

prom_targets({
  state?: "active" | "dropped",
  job?: string
})

Returns:

{
  "targets": [
    {
      "job": "api",
      "instance": "api-1:8080",
      "health": "up",
      "last_scrape": "2025-12-29T10:29:45Z",
      "scrape_duration": "0.023s",
      "error": null
    }
  ],
  "summary": "12 of 12 targets healthy"
}

Discovery

prom_metadata

Get metric metadata (help, type, unit).

prom_metadata({
  metric?: string,          // specific metric (omit for all)
  limit?: number
})

Analysis

prom_analyze

AI-powered metric analysis.

prom_analyze({
  query: string,
  question?: string,        // "Is this normal?", "What caused the spike?"
  use_ai?: boolean
})

Returns:

{
  "query": "rate(http_errors_total[5m])",
  "data_summary": {
    "current": 12.3,
    "1h_ago": 2.1,
    "change": "+486%"
  },
  "synthesis": {
    "analysis": "Error rate spiked 5x in the last hour. The spike correlates with deployment at 10:15. Errors are concentrated on /api/checkout endpoint.",
    "suggested_queries": [
      "rate(http_errors_total{handler=\"/api/checkout\"}[5m])",
      "histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m]))"
    ],
    "confidence": "high"
  }
}

prom_suggest_query

Get PromQL query suggestions.

prom_suggest_query({
  intent: string            // "show me api latency p99"
})

NEVERHANG Architecture

PromQL queries can be expensive. High-cardinality queries can OOM Prometheus.

Query Timeouts

• Default: 30s
• Configurable per-query
• Server-side timeout parameter

Cardinality Protection

• Limit series returned
• Block known expensive patterns
• Warn on high-cardinality queries

Circuit Breaker

• 3 timeouts in 60s → 5 minute cooldown
• Tracks Prometheus health
• Graceful degradation

{
  "neverhang": {
    "query_timeout": 30000,
    "max_series": 1000,
    "circuit_breaker": {
      "failures": 3,
      "window": 60000,
      "cooldown": 300000
    }
  }
}

Fallback AI

Optional Haiku for metric analysis.

{
  "fallback": {
    "enabled": true,
    "model": "claude-haiku-4-5",
    "api_key_env": "PROM_MCP_FALLBACK_KEY",
    "max_tokens": 500
  }
}

When used:

• prom_analyze with questions
• prom_suggest_query for natural language
• Anomaly detection

Configuration

~/.config/prometheus-mcp/config.json:

{
  "prometheus": {
    "url": "http://localhost:9090",
    "auth": {
      "type": "none"
    }
  },
  "permissions": {
    "query": true,
    "alerts": true,
    "admin": false
  },
  "query_limits": {
    "max_duration": "30s",
    "max_series": 1000
  },
  "fallback": {
    "enabled": false
  }
}

Claude Code Integration

{
  "mcpServers": {
    "prometheus": {
      "command": "prometheus-mcp",
      "args": ["--config", "/path/to/config.json"]
    }
  }
}

Installation

npm install -g @arktechnwa/prometheus-mcp

Requirements

• Node.js 18+
• Prometheus server (2.x+)
• Optional: Anthropic API key for fallback AI

Credits

Created by Claude (claude@arktechnwa.com) in collaboration with Meldrey. Part of the ArktechNWA MCP Toolshed.