Available Agents and MCP Servers
🤖Available Agents
Kubernetes Agent
Multi-domain lifecycle automation (k8s-autopilot) — Helm chart generation, active cluster operations, ArgoCD onboarding, observability setup, and cluster diagnostics. Powered by the Deep Agent pattern with Human-in-the-Loop safety gates.
View Documentation →CI-Copilot
Multi-agent framework that generates, modifies, and debugs CI/CD pipelines through conversation. Scans repositories for context, infers CI intent, validates against security policies, and renders production-ready GitHub Actions YAML with approval gates.
View Documentation →AWS Orchestrator
Autonomous multi-agent system with 7+ specialized sub-agents that generates enterprise-grade AWS Terraform modules. Features deep research analysis, A2A protocol integration, security compliance validation, and production-ready IaC output.
View Documentation →SRE Agent
Incident commander and cross-agent coordination layer. Orchestrates triage across K8s, cloud, and monitoring agents. Executes runbooks, tracks SLO/error budgets, conducts post-incident analysis, and reduces operational toil through intelligent automation.
View Documentation →🔌Available MCP Servers
Helm MCP Server
Full Helm chart lifecycle management — repository operations, release management, values configuration, and rollback capabilities. 18 tools for comprehensive Helm operations.
View Documentation →ArgoCD MCP Server
GitOps-powered continuous deployment — application sync, health monitoring, rollback support, and multi-cluster management. 29 tools for complete ArgoCD control.
View Documentation →Argo Rollout MCP Server
Progressive delivery lifecycle for Kubernetes — convert Deployments to Rollouts, orchestrate canary and blue-green deployments, promote or abort rollouts, and integrate Prometheus analysis.
View Documentation →
Traefik MCP Server
AI-driven Kubernetes edge traffic management — weighted canary routing, middleware generation, traffic mirroring, TCP routing, and automated NGINX-to-Traefik migrations. 11 tools + 12 resources.
View Documentation →Terraform MCP Server
Secure Infrastructure as Code operations — semantic document search, intelligent ingestion, and enterprise-grade execution. Multi-provider AI support with Neo4j integration.
View Documentation →Prometheus MCP Server
Full Prometheus lifecycle management — safe PromQL execution with counter enforcement, exporter deployment (19 exporters), rule authoring and simulation, TSDB FinOps, and multi-backend support. 28 tools + 14 resources.
View Documentation →Alertmanager MCP Server
Alert triage, silence lifecycle management with safety guardrails, routing introspection and simulation, governance audit trails, and notification pipeline testing. 14 tools + 11 resources.
View Documentation →Coming Soon
Azure Orchestrator
Multi-agent system for Azure infrastructure automation. Generates enterprise-grade Bicep and Terraform modules for AKS clusters, Azure Functions, Cosmos DB, and Azure-native networking. Features deep research analysis against Azure best practices with compliance-first architecture.
GCP Orchestrator
Multi-agent system for Google Cloud infrastructure automation. Generates production-ready Terraform modules for GKE clusters, Cloud Run services, BigQuery, and GCP-native networking. Leverages Google Cloud best practices with cost optimization and security-first defaults.
Monitoring Agent
Non-Kubernetes observability orchestrator for multi-cloud environments. Integrates with Datadog, CloudWatch, New Relic, and other SaaS monitoring platforms. Automates dashboard generation, alert configuration, anomaly detection, and cross-signal correlation across metrics, logs, and traces.
Use Cases
Conversational DevOps
Ship faster with intent-based deployments.
- Propose: Agents draft complete CI/CD pipelines from simple commands.
- Approve: Review and merge changes via standard GitOps workflows.
- Audit: Maintain 100% visibility and control over every release.
Intelligent SRE Operations
Resolve incidents before they impact customers.
- Investigate: Agents autonomously root-cause latency and errors.
- Remediate: Execute safe fixes within pre-defined guardrails.
- Escalate: Route critical issues to experts with full context.
Multi-Cloud Command Center
Unify AWS, Azure, and GCP under one control plane.
- Abstract: Define infrastructure once; deploy anywhere without silos.
- Optimize: Cross-cloud analysis for cost, performance, and placement.
- Standardize: Enforce consistent compliance across all your clouds.
Kubernetes Orchestration
Expert-level K8s management via natural language.
- Manage: Autonomously handle pods, resources, and versions.
- Safeguard: Low-risk tasks auto-run; high-risk tasks await approval.
- Deploy: Execute Blue/Green and Canary rollouts with zero downtime.
Compliance Automation
Continuous audit readiness, minimal toil.
- Monitor: Real-time tracking of access, config changes, and logs.
- Collect: Auto-gather evidence from AWS, K8s, and security tools.
- Verify: Have 12 months of audit-proven evidence always ready.
How It Works
Get From Zero to Operational
in Three Phased Steps + Guardrails Built In
Connect Your Clouds
Securely connect your AWS, Azure, and GCP accounts. Configure credentials, IAM policies, and validate compliance.
- Standard Setups: Rapid integration via secure, read-only initial access.
- Regulated Industries: Native support for HIPAA/SOC 2 governance validation.
- Result: Agents gain secure, audited access across all infrastructure.
Deploy Specialized Agents
Roll out specialized agents in phases. Start with read-only observability, then advisory assistants.
- Training: Agents learn your specific cloud patterns, tools, and workflows.
- Gradual Autonomy: Start with routine tasks; progress to complex orchestration.
- Security: Governance and safety checks embedded at every stage.
Start Talking to Your Infrastructure
Command via natural language. Review plans in Git, approve, and let agents execute your intent.
- Routine Ops: Low-risk actions (scaling, restarts) execute with notifications.
- Critical Ops: Deployments and migrations wait for your Git-based approval.
- Collaborative: Human control. Machine efficiency. Fully audited and rollback-able.
Technology
Powered by LangGraph Multi-Agent Architecture
Autonomous Reasoning with Built-In Governance
Conversational AI Engine
Domain-Specialized Conversational AI Engine. Deep learning trained for infrastructure operations.
- Intent Recognition: Parse infrastructure requests.
- Entity Extraction: Identify resources, targets, parameters.
- Context Awareness: Understand multi-cloud environments.
- Safety Validation: Check permissions before execution.
Multi-Agent Framework
LangGraph Multi-Agent Orchestration Framework. Specialized agents collaborate with built-in governance.
- Supervisor directs execution (central coordinator).
- Agents communicate via shared immutable state.
- Each operation is a checkpointed node in a DAG.
- Guardrails (Prevent Harm): Input/Output validation, constraint enforcement.
- Permissions (Control Power): Role-based access, boundaries, approvals.
- Auditability (Ensure Accountability): Decision history, change tracking, rollbacks.
Universal Cloud Integration
Works seamlessly across AWS, Azure, GCP, Kubernetes, bare metal, on-premises.
- Unified API Gateway: Single interface for all clouds.
- Infrastructure-as-Code Layer: Terraform-based abstraction.
- Kubernetes Control Plane: Container orchestration.
- Credential Management: Unified IAM and authentication.
Result: No vendor lock-in. Deploy once, run anywhere with complete control.
Intelligent IaC
Autonomous Execution Through Infrastructure-as-Code
- Multi-agent orchestration layer DECIDES what infrastructure to create.
- Then it VALIDATES through GitOps and EXECUTES via Terraform/CloudFormation.
"The orchestration layer is the hero. IaC generation is supporting infrastructure."
Need Help Getting Started?
We help teams integrate AI automation into their existing DevOps stack — no rip-and-replace required. Your tools, your environment, your data.
DevOps Assessment
We audit your toolchain, find where your team spends the most time on repetitive work, and deliver a practical roadmap
AI Agent Integration
We deploy agents configured for your stack — integrated with your existing tools, not replacing them
Team Enablement
We transfer full ownership to your team. Our goal is to work ourselves out of a job