MCP 服务器

Kubernetes + Prometheus SRE MCP Server

Enables natural language Kubernetes cluster operations, SLO monitoring, and PromQL queries via Claude using the Model Context Protocol.

README

🤖 Kubernetes + Prometheus SRE MCP Server — natural language cluster ops, SLO monitoring, and PromQL queries via Claude

Natural language Kubernetes operations — powered by Model Context Protocol (MCP)
Built to scale from a single cluster to multi-cluster, multi-team enterprise environments.

🎯 What Is This?

An MCP (Model Context Protocol) server that exposes Kubernetes SRE operations as tools an AI assistant can call.

You:    "Run the high error rate runbook for the production namespace"

Claude: [calls run_runbook → executes org-approved diagnosis sequence]
        Step 1: Checked deployments — nginx (3/3), api-service (1/3 ⚠️)
        Step 2: Found pod api-service-7f9d — 47 restarts, OOMKilled
        Step 3: Warning events — OOMKilled x3 in last 10 minutes
        Recommendation: Increase memory limit to 512Mi + scale to 5 replicas

✨ What's New in v2.0

Feature	v1	v2
Clusters supported	1 (hardcoded)	Many (dynamic context switching)
Write operations	Unrestricted	Policy-checked with guardrails
Audit trail	None	Full structured JSON log
Incident diagnosis	Ad-hoc	Encoded runbooks (standardized)
Operational consistency	Per-engineer	Org-wide enforced

🛠️ Tools

Read

Tool	Description
`list_clusters`	All clusters in kubeconfig
`get_pods`	Pod status, restarts, container states
`get_crashlooping_pods`	CrashLoopBackOff pods across all namespaces
`get_pod_logs`	Logs including previous crashed container
`get_node_health`	Node readiness and pressure conditions
`get_deployments`	Desired vs ready vs available replicas
`get_events`	Warning events — key incident signal
`get_namespaces`	All namespaces

Write (Policy-checked + Audit-logged)

Tool	Policy Enforced
`scale_deployment`	Max replicas · Blocked namespaces · Prod minimums

SRE Runbooks

Tool	Description
`list_runbooks`	Available runbooks with triggers
`run_runbook`	Execute org-standard diagnosis sequence

Governance

Tool	Description
`get_audit_log`	All recent operations with timestamps

🏗️ Architecture

Claude Desktop (MCP Host)
       │
       │  MCP Protocol (stdio / JSON-RPC)
       ▼
┌─────────────────────────────────────┐
│         SRE MCP Server v2           │
│  server.py        ← entry point     │
│  cluster_manager  ← multi-cluster   │
│  policy.py        ← write guards    │
│  audit.py         ← JSON audit log  │
│  runbooks.py      ← SRE runbooks    │
└──────────────┬──────────────────────┘
               │  kubernetes Python SDK
               ▼
    ┌──────────────────────┐
    │  Kubernetes Clusters │
    │  (any kubeconfig     │
    │   context)           │
    └──────────────────────┘

🚀 Quick Start

git clone https://github.com/ManishMaurya22/sre-mcp-server
cd sre-mcp-server
python3.11 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "sre-k8s": {
      "command": "/Users/<YOUR_USERNAME>/sre-mcp-server/venv/bin/python",
      "args": ["/Users/<YOUR_USERNAME>/sre-mcp-server/server.py"]
    }
  }
}

See docs/SETUP.md for full setup guide.

🔐 Policy Configuration

export POLICY_MAX_REPLICAS=30
export POLICY_SCALE_BLOCKED_NS="kube-system,gatekeeper-system"
export POLICY_PROD_NAMESPACES="production,prod"
export POLICY_PROD_MIN_REPLICAS=2

You:    "Scale nginx to 0 in production"
Claude: ❌ Policy Denied — scaling to 0 not allowed in production (min: 2)
        Operation audit-logged.

📋 Encoded Runbooks

Available: high_error_rate · node_pressure · deployment_rollback

You: "Run the high_error_rate runbook for production"

Claude runs in order:
  1. get_deployments    → spot unhealthy deployments
  2. get_pods           → check restart counts
  3. get_events         → surface warning signals
  4. get_crashlooping_pods → cluster-wide check
  + surfaces remediation hints

🗂️ Structure

sre-mcp-server/
├── server.py              # Main MCP server
├── cluster_manager.py     # Multi-cluster context management
├── policy.py              # Write operation guardrails
├── audit.py               # Structured audit trail
├── runbooks.py            # Encoded SRE runbooks
├── requirements.txt
├── tools/k8s_tools.py
├── config/claude_desktop_config.example.json
├── docs/
│   ├── SETUP.md
│   └── INTERVIEW_GUIDE.md
└── .github/workflows/ci.yaml