Use the MCP server

Once the MCP server is installed, your coding agent can ask NOFire AI about production without leaving the editor.

Available tools

Once configured, these tools are available to your AI assistant:

Tool	Use when
`nofire_search_entities`	Discovering what infrastructure exists or verifying entity names
`nofire_get_entity_dependencies`	Understanding upstream/downstream service topology
`nofire_get_entity_changes`	Checking what changed recently (infra changes + VCS activity)
`nofire_get_entity_metrics`	Finding available Prometheus metrics and PromQL queries
`nofire_assess_deployment_risk`	Scoring risk before deploying changes
`nofire_analyze_blast_radius`	Understanding cascading failure impact
`nofire_find_related_incidents`	Checking incident history and root cause patterns
`nofire_get_cluster_summary`	Getting cluster-wide health overview
`nofire_get_recent_deploys`	Seeing cluster-wide deploy + VCS timeline

Shift-left / proactive reliability

Assess Deployment Risk

Score deployment risk for a service before merging:Example:

What's the deployment risk for payment-service in prod?

Uses nofire_assess_deployment_risk to calculate a weighted risk score (0-100) based on blast radius, dependency depth, incident history, and recent change velocity.Risk levels: LOW (0-39), MEDIUM (40-59), HIGH (60-79), CRITICAL (80-100).

Analyze Blast Radius

Understand cascading impact of service failures:Example:

What's the blast radius if payment-service fails?

Uses nofire_analyze_blast_radius to traverse the dependency graph and show direct + transitive impact.

Cluster Summary

Get a cluster-wide health overview when you do not know where to start:Example:

Give me a summary of the prod cluster in the last 6 hours

Uses nofire_get_cluster_summary to show entity counts, top problematic services, and recent alert investigations.

Incident response & RCA

Discover Entities

Find services, pods, deployments in your cluster:Example:

Show me all services with "payment" in the name

Uses nofire_search_entities with partial name matching.

Get Entity Changes + VCS Activity

View recent infrastructure changes and correlated VCS activity (commits, PRs):Example:

What changed in payment-service in the last 6 hours?

Uses nofire_get_entity_changes which returns deployments, configuration updates, scaling events, plus merged PRs and pushes in the same time window.

Recent Deploys Timeline

See cluster-wide deploy and change timeline:Example:

Show me all deploys in prod in the last 24 hours

Uses nofire_get_recent_deploys to show a chronological timeline of infra changes + VCS events across the cluster.

Check incident history and root cause patterns:Example:

Has payment-service had incidents in the last 30 days?

Uses nofire_find_related_incidents with confidence filtering (only high-confidence root causes).

Get Dependencies

Explore service dependencies:Example:

What services does payment-service depend on?

Uses nofire_get_entity_dependencies to show upstream and downstream connections.

Usage examples

Pre-merge risk assessment

Scenario: You have modified payment processing code and want to assess risk before creating a PR. In Cursor:

I've modified these files:
- src/services/payment/stripe-client.ts
- src/services/payment/processor.ts
- src/api/payment-routes.ts

Can you assess the deployment risk using NOFire AI?

Cursor Response:

I've analyzed your changes using NOFire AI:

Affected Services: 1 (payment-service)

Risk Assessment:
  Overall Risk: 0.82 (HIGH)
  
  Risk Breakdown:
    - Blast Radius: 0.85 (15 services affected)
    - Payment processing is on critical path
    - Dependency depth: 2 (mid-level service)
    - Recent stability: 0.70
  
  Deployment Strategy:
    ⚠️  HIGH RISK - Staged deployment mandatory
    
    1. Deploy to staging environment first
    2. Run full payment test suite
    3. Deploy to production with canary (5% traffic)
    4. Monitor for 2 hours before full rollout
    5. Notify #payments and #platform teams
    
  Critical Services in Blast Radius:
    - api-gateway (entry point)
    - billing-service (financial impact)
    - refund-service (payment flow)
    
  Recommendation: Schedule deployment during low-traffic window
  with team available for monitoring.

Onboarding New engineers

Scenario: New team member needs to understand the production architecture. In Cursor:

I'm new to this codebase. Can you use NOFire AI to show me:
1. What services we have in production
2. How the payment flow works (service dependencies)

Cursor Response:

I've queried NOFire AI about your production environment:

Services in Production (showing payment-related):
  - api-gateway (entry point for all traffic)
  - payment-service (core payment processing)
  - billing-service (invoicing and subscriptions)
  - stripe-integration-service (payment provider)
  - notification-service (payment confirmations)
  - audit-service (transaction logging)

Payment Flow Dependencies:
  
  api-gateway
    ↓ calls
  payment-service
    ↓ depends on
    ├─ stripe-integration-service (payment processing)
    ├─ billing-service (invoice creation)
    ├─ notification-service (customer emails)
    └─ audit-service (compliance logging)

Critical Services to be careful with:
  - payment-service: 15 services depend on this
  - api-gateway: Entry point, affects all traffic
  
Would you like me to explain what each service does or show
recent changes to any of them?

Investigating Production behavior

Scenario: A service has been flaky, you want to understand what changed. In Claude Desktop:

Using NOFire AI, what changes happened to user-service 
in the last 24 hours?

Claude Response:

I've queried NOFire AI for recent changes to user-service:

Recent Changes (last 24 hours):
  
  1. Deployment (14 hours ago)
     - Image: user-service:v2.1.4 → v2.1.5
     - Type: Rolling update
     - Status: Completed
  
  2. Configuration Change (8 hours ago)
     - ConfigMap updated: database connection pool
     - MAX_POOL_SIZE: 20 → 50
  
  3. Pod Restart (3 hours ago)
     - 2 pods restarted due to OOMKilled
     - Memory limit hit
  
  4. Scaling Event (1 hour ago)
     - Replicas: 3 → 5
     - Reason: High CPU usage

Potential Issues:
  - Memory limit may be too low after config change
  - Connection pool increase might be causing memory pressure
  - Recent scaling event suggests ongoing performance issues

Would you like me to analyze these changes for root cause?

Best practices

Check Risk Before Every Merge

Make it a habit to check deployment risk before you create or approve a pull request.

Use NOFire AI for Onboarding

New team members can ask NOFire AI about production:

“What services do we have in production?”
“How does auth-service connect to user-service?”
“What changed in payment-service this week?”

Makes production knowledge accessible without tribal knowledge bottlenecks.

Include Context in Queries

Provide context about what you are doing:❌ “Check risk” ✅ “I am updating payment API error handling. What is the deployment risk?”❌ “What changed?” ✅ “What changed in auth-service in the last 24 hours?”

Use for Incident Investigation

When something breaks, ask NOFire AI:

“What changed in [service] before the incident?”
“Analyze [service] changes from 2 hours ago”
“What services depend on [broken-service]?”

Speeds up incident response by making telemetry data queryable.

Bonus: Automate with AGENTS.md

Make NOFire AI checks automatic by adding them to your AGENTS.md file. AI coding agents then always use NOFire AI for deployment risk and operational knowledge. Create or update AGENTS.md in your repository root:

# AGENTS.md

## NOFire AI MCP Integration

This project uses NOFire AI for deployment risk assessment and production knowledge.
NOFire AI MCP server is available in your IDE.

## When to use NOFire AI

**Automatically use NOFire AI in these scenarios:**

### Before Deployment (Shift-Left)
1. **Before completing any task** - Always assess deployment risk
2. **When modifying services** - Understand which production services are affected
3. **Before suggesting a merge**: check that it is safe to deploy
4. **On refactoring** - Check blast radius and dependency impact

### Production Knowledge (Anytime)
5. **When user asks about production** - Answer with real production data
6. **During incident investigation** - Find what changed recently
7. **For onboarding new engineers** - Help understand production architecture
8. **When debugging** - Query service dependencies and recent changes

## Required Pre-Merge Workflow

Before marking any task complete or suggesting a merge:

1. Run tests
2. **Discover affected entities:**
   ```
   nofire_search_entities(name="payment", cluster="prod")
   ```
3. **Assess deployment risk:**
   ```
   nofire_assess_deployment_risk(entity_name="payment-service", cluster="prod")
   ```
4. **Show the user** the risk score and recommendations
5. **For HIGH/CRITICAL risk**, check blast radius:
   ```
   nofire_analyze_blast_radius(entity_name="payment-service", cluster="prod")
   ```

## Risk score interpretation

- **CRITICAL (80-100)**: Peer review + feature flags required. Never deploy Fridays.
- **HIGH (60-79)**: Staged rollout, deploy during business hours with team available.
- **MEDIUM (40-59)**: Consider canary rollout (10% → 50% → 100%).
- **LOW (0-39)**: Standard deployment is safe.

## Available NOFire AI MCP Tools

| Tool | Use when |
|------|----------|
| `nofire_search_entities` | Discovering what infrastructure exists or verifying entity names |
| `nofire_get_entity_dependencies` | Understanding upstream/downstream service topology |
| `nofire_get_entity_changes` | Checking what changed recently (infra + VCS activity) |
| `nofire_get_entity_metrics` | Finding available Prometheus metrics and PromQL queries |
| `nofire_assess_deployment_risk` | Scoring risk before deploying changes |
| `nofire_analyze_blast_radius` | Understanding cascading failure impact |
| `nofire_find_related_incidents` | Checking incident history and root cause patterns |
| `nofire_get_cluster_summary` | Getting cluster-wide health overview (start here if unsure) |
| `nofire_get_recent_deploys` | Seeing cluster-wide deploy + VCS timeline |

## Connecting code to production

1. Use `nofire_get_entity_changes` or `nofire_get_recent_deploys` to find commit SHAs and PR references
2. Search the codebase for those commits to understand the code diff
3. Cross-reference with `nofire_find_related_incidents` to check if similar changes caused issues before

## When NOT to Use NOFire AI

Skip NOFire AI for:
- Documentation-only changes (*.md files)
- Test-only changes (no production code modified)
- Local development config (non-production)
- README updates, comment changes

## Critical Rule

**Always call NOFire AI before suggesting a merge that modifies production code.**

Why this works:

Works with Cursor, GitHub Copilot, Jules, Aider, and most AI coding agents
Makes shift-left and operational knowledge automatic
Entire team follows same safety checks and has access to production knowledge

Next steps

Troubleshooting

The server does not appear, a tool returns nothing, or a token is rejected.

Deployment risk

What NOFire AI checks before you deploy.

Get Started

Production readiness

Change management

Incidents

Always-On Workflows

Analytics

Setup & Integrations

Security

Use the MCP server

Available tools

Shift-left / proactive reliability

Incident response & RCA

Usage examples

Pre-merge risk assessment

Onboarding New engineers

Investigating Production behavior

Best practices

Bonus: Automate with AGENTS.md

Next steps

Troubleshooting

Deployment risk

​Available tools

​Shift-left / proactive reliability

​Incident response & RCA

​Usage examples

​Pre-merge risk assessment

​Onboarding New engineers

​Investigating Production behavior

​Best practices

​Bonus: Automate with AGENTS.md

​Next steps

Troubleshooting

Deployment risk

Available tools

Shift-left / proactive reliability

Incident response & RCA

Usage examples

Pre-merge risk assessment

Onboarding New engineers

Investigating Production behavior

Best practices

Bonus: Automate with AGENTS.md

Next steps