Mcp

Kubeshark indexes cluster-wide network traffic at the kernel level using eBPF — delivering instant answers to any query using network, API, and Kubernetes semantics.

What you can do:

• Download Retrospective PCAPs — cluster-wide packet captures filtered by nodes, time, workloads, and IPs. Store PCAPs for long-term retention and later investigation.
• Visualize Network Data — explore traffic matching queries with API, Kubernetes, or network semantics through a real-time dashboard.
• See Encrypted Traffic in Plain Text — automatically decrypt TLS/mTLS traffic using eBPF, with no key management or sidecars required.
• Integrate with AI — connect your favorite AI assistant (e.g. Claude, Copilot) to include network data in AI-driven workflows like incident response and root cause analysis.

Get Started

helm repo add kubeshark https://helm.kubeshark.com
helm install kubeshark kubeshark/kubeshark
kubectl port-forward svc/kubeshark-front 8899:80

Open http://localhost:8899 in your browser. You're capturing traffic.

For production use, we recommend using an ingress controller instead of port-forward.

Connect an AI agent via MCP:

brew install kubeshark
claude mcp add kubeshark -- kubeshark mcp

MCP setup guide →

Network Data for AI Agents

Kubeshark exposes cluster-wide network data via MCP — enabling AI agents to query traffic, investigate API calls, and perform root cause analysis through natural language.

"Why did checkout fail at 2:15 PM?" "Which services have error rates above 1%?" "Show TCP retransmission rates across all node-to-node paths" "Trace request abc123 through all services"

Works with Claude Code, Cursor, and any MCP-compatible AI.

MCP setup guide →

AI Skills

Open-source, reusable skills that teach AI agents domain-specific workflows on top of Kubeshark's MCP tools:

Install as a Claude Code plugin:

/plugin marketplace add kubeshark/kubeshark
/plugin install kubeshark

Or clone and use directly — skills trigger automatically based on conversation context.

AI Skills docs →

Query with API, Kubernetes, and Network Semantics

Kubeshark indexes cluster-wide network traffic by parsing it according to protocol specifications, with support for HTTP, gRPC, Redis, Kafka, DNS, and more. A single KFL query can combine all three semantic layers — Kubernetes identity, API context, and network attributes — to pinpoint exactly the traffic you need. No code instrumentation required.

KFL reference → · Traffic indexing →

Workload Dependency Map

A visual map of how workloads communicate, showing dependencies, traffic volume, and protocol usage across the cluster.

Learn more →

Traffic Retention & PCAP Export

Capture and retain raw network traffic cluster-wide, including decrypted TLS. Download PCAPs scoped by time range, nodes, workloads, and IPs — ready for Wireshark or any PCAP-compatible tool. Store snapshots in cloud storage (S3, Azure Blob, GCS) for long-term retention and cross-cluster sharing.

Snapshots guide → · Cloud storage →

Features

Install

Installation guide →

Contributing

We welcome contributions. See CONTRIBUTING.md.

License

Apache-2.0