incident-commander-mcp

AI-powered incident management MCP server built for the NitroStack Hackathon.

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⚠️ R12 Disclosure — Simulated Integrations

All data returned by this MCP server is entirely mocked and stored in-memory.

There are NO real connections to:

• Kubernetes / container orchestration platforms
• Grafana / Prometheus / any metrics backend
• GitHub / GitLab / any version control system
• PagerDuty / OpsGenie / any alerting system
• Stripe or any payment processor

This is a demo for hackathon evaluation purposes. The realistic-looking data is seeded with a purposeful incident scenario (deploy at 14:02 → error spike at 14:03) to demonstrate agent reasoning capabilities over MCP tools, resources, and prompts.

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Overview

incident-commander-mcp is a single MCP server built on the NitroStack TypeScript framework (@nitrostack/core). It exposes tools, resources, and prompts that enable an AI agent to:

1. Investigate production incidents by querying deployment history, error logs, and metrics
2. Reason about root causes using cross-correlated data
3. Act (with human approval) by requesting rollbacks or creating incident tickets
4. Document incidents via structured postmortem prompts

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Capabilities

🔧 Tools (8)

Tool	Description	Annotation
get_recent_deployments	Recent deployments, optionally filtered by service	readOnly
get_service_logs	Error logs for a service within a time window	readOnly
get_service_metrics	Latency, error rate, CPU/memory time-series	readOnly
check_pod_status	Kubernetes pod readiness and restart counts	readOnly
analyze_root_cause	Cross-correlates deploy + logs + metrics → hypothesis	readOnly
trigger_rollback	Submits a rollback request (requires human approval)	destructive
create_incident_ticket	Creates a new in-memory incident record	—
post_status_update	Appends a timeline entry to an incident	—

📦 Resources (4)

URI	Description
incident://current	Active incident snapshot (JSON)
incident://{id}/timeline	Timeline for a specific incident
deployments://recent	Last 20 deployments across all services
service://{name}/health	Health snapshot for one service

💬 Prompts (3)

Prompt	Arguments	Description
root_cause_investigation	service, symptom	Guides structured RCA with tool call sequence
postmortem_report	incident_id	Generates a blameless postmortem
rollback_decision	service, target_version	Risk/benefit analysis before rollback

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Incident Scenario (Demo)

The seeded data tells a realistic story:

14:00 UTC  — payment-service healthy: error_rate 0.2%, latency 45ms
14:02 UTC  — payment-service v2.4.1 deployed (commit a3f8c21d)
14:03 UTC  — Error spike: "Cannot read properties of undefined (reading 'stripeId')"
14:03 UTC  — error_rate jumps to 28%, latency spikes to 320ms
14:04 UTC  — Pods begin CrashLoopBackOff, 7 restarts
14:05 UTC  — error_rate: 91%, latency: 1450ms, API Gateway circuit breaker opens

An agent reasoning over get_recent_deployments → get_service_logs → get_service_metrics → analyze_root_cause should produce a hypothesis pointing to v2.4.1 as the culprit with ~0.90 confidence.

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Quick Start

# 1. Clone / navigate to project
cd incident-commander-mcp

# 2. Install dependencies (already done by CLI)
npm install

# 3. Start development server
npm run dev

Building for Production

npm run build
npm start

Built with NitroStack ⚡