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Claude Log Analyzer

mcp-samarthpatel24-claude-log-analyzer · by samarthpatel24

MCP server for Kubernetes log analysis, anomaly detection, and root cause analysis with Claude Code

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Install

$ agentstack add mcp-samarthpatel24-claude-log-analyzer

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

MCP server that connects to your Kubernetes cluster and provides Claude Code with tools for log analysis, anomaly detection, and root cause analysis.


What it does

  • Fetches pod logs, status, metrics, and events from a live K8s cluster
  • Detects anomalies: CPU/memory spikes, error bursts, restart storms, OOM kills
  • Correlates events across services to identify cascading failures
  • Produces evidence-backed root cause analysis reports (MD or TXT)
  • Every finding cites actual log lines, metric values, or event data

Install

Add to your project's .mcp.json:

{
  "mcpServers": {
    "k8s-analyzer": {
      "command": "npx",
      "args": ["-y", "claude-log-analyzer"]
    }
  }
}

> Windows users: Use "command": "cmd" with "args": ["/c", "npx", "-y", "claude-log-analyzer"]

Prerequisites

  • A valid kubeconfig (~/.kube/config or set KUBECONFIG env var)
  • RBAC permissions to read pods, logs, events, and metrics
  • metrics-server on the cluster (optional, for resource metrics)

Tools

| Tool | Description | |------|-------------| | list_namespaces | List all namespaces in the cluster | | fetch_pod_logs | Fetch and filter pod logs with severity detection and noise removal | | get_pod_status | Pod phase, conditions, container states, restart counts | | get_resource_metrics | CPU/memory usage via Metrics API with % against limits | | get_events | Kubernetes events (Warning/Normal) with filtering | | get_cluster_health | High-level cluster health overview | | detect_anomalies | Run anomaly detection on a namespace | | analyze_service | Deep dive on a specific service | | get_root_cause_analysis | Full RCA with exported report |

Configuration

Environment variables

| Variable | Default | Description | |----------|---------|-------------| | KUBECONFIG | ~/.kube/config | Path to kubeconfig file | | K8S_CONTEXT | current-context | Kubernetes context to use | | K8S_DEFAULT_NAMESPACE | default | Default namespace | | K8S_LOG_MAX_LINES | 500 | Max log lines per pod | | K8S_TIME_WINDOW | 60 | Default time window in minutes | | K8S_MODE | both | Default mode: logs, metrics, or both |

Pass env vars through MCP config:

{
  "mcpServers": {
    "k8s-analyzer": {
      "command": "npx",
      "args": ["-y", "claude-log-analyzer"],
      "env": {
        "KUBECONFIG": "/path/to/kubeconfig",
        "K8S_TIME_WINDOW": "30",
        "K8S_MODE": "logs"
      }
    }
  }
}

Per-call configuration

Every analysis tool accepts:

  • timeWindowMinutes — override the default time window
  • mode"logs", "metrics", or "both"

The get_root_cause_analysis tool also accepts:

  • exportFormat"md" (default) or "txt"
  • exportPath — custom file path for the report

Token efficiency

The server minimizes token usage by:

  • Filtering out noise (health checks, liveness/readiness probes)
  • Detecting log severity to skip irrelevant lines
  • Summarizing log results (error counts, top errors) alongside raw data
  • Truncating with a truncated flag so Claude can narrow queries
  • Returning only a summary from the RCA tool (full details go to the exported report)

Anomaly detection

  • CPU/memory spikes — peer comparison (z-score against sibling pods) + threshold-based (% of limit)
  • Error bursts — 1-minute bucketing, flags statistical outliers (mean + 3σ) and absolute thresholds
  • Restart storms — restart count thresholds + CrashLoopBackOff detection
  • OOM kills — container termination reason + event scanning
  • Event floods — warning event count per object with auto-escalation for critical reasons

Report output

Reports are written to disk, not returned in full to the LLM. Every claim is backed by evidence:

### [CRITICAL] OOM Kill — pod/payments-7f8b9-x2k4
- **Description:** Container 'payments' was OOM killed (exit code: 137)
- **Value:** 7 (threshold: 3)

### [HIGH] Error Burst — pod/payments-7f8b9-x2k4
- **Description:** 142 errors/min detected (baseline: 3.0/min). 284 total errors in window.
- **Sample log lines:**
  - `java.lang.OutOfMemoryError: Java heap space`
  - `Failed to process transaction: heap exhausted`

License

[MIT](LICENSE)

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.