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kubeshark / Subagents · Registry oficial

kubeshark

eBPF-powered network observability for Kubernetes. Indexes L4/L7 traffic with full K8s context, decrypts TLS without keys. Queryable by AI agents via MCP and humans via dashboard.

  • 12.1k estrellas
  • 552 forks
  • 141 issues abiertos
  • Lenguaje: Go
  • Licencia: Apache-2.0
  • actualizado

Instalación

Terminal
git clone https://github.com/kubeshark/kubeshark && cp kubeshark/*.md ~/.claude/agents/
  1. Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
  2. Start a new Claude Code session to load the agents.
  3. Delegate work to them with the Task/Agent tool or by name.

Nota editorial

Kubeshark is a Kubernetes network observability tool written in Go that captures and indexes cluster-wide L4/L7 traffic at the kernel level using eBPF, requiring no code instrumentation or sidecar proxies. It automatically decrypts TLS and mTLS traffic without key management, parses protocols including HTTP, gRPC, Redis, Kafka, and DNS, and stores retrospective PCAPs that can be scoped by time range, workloads, nodes, and IPs for export to Wireshark or cloud storage (S3, Azure Blob, GCS). The tool connects to Claude via MCP using a two-command setup (`kubeshark mcp` registered through `claude mcp add`), enabling Claude Code and other MCP-compatible agents to query live traffic in natural language for incident response and root cause analysis. It also ships two installable Claude Code plugins called AI Skills: Network RCA, which handles snapshot extraction and trend comparison, and KFL, which writes and debugs queries in Kubeshark Filter Language. SREs, platform engineers, and AI-driven workflows investigating production incidents are the primary audience.

Items instalables

4 items en este repositorio

installSkill

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kflSkill

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README

Resumen de Subagents

README completo en GitHub

Network Observability for SREs & AI Agents

Live Demo · Docs


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.

Kubeshark


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 Demo

MCP setup guide →

AI Skills

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

SkillDescription
Network RCARetrospective root cause analysis — snapshots, dissection, PCAP extraction, trend comparison
KFLKFL (Kubeshark Filter Language) expert — writes, debugs, and optimizes traffic filters

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 query combining API, Kubernetes, and network semantics

KFL reference → · Traffic indexing →

Workload Dependency Map

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

Service Map

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.

Traffic Retention

Snapshots guide → · Cloud storage →


Features

FeatureDescription
Traffic SnapshotsPoint-in-time snapshots with cloud storage (S3, Azure Blob, GCS), PCAP export for Wireshark
Traffic IndexingReal-time and delayed L7 indexing with request/response matching and full payloads
Protocol SupportHTTP, gRPC, GraphQL, Redis, Kafka, DNS, and more
TLS DecryptioneBPF-based decryption without key management, included in snapshots
AI IntegrationMCP server + open-source AI skills for network RCA and traffic filtering
KFL Query LanguageCEL-based query language with Kubernetes, API, and network semantics
100% On-PremisesAir-gapped support, no external dependencies

Install

MethodCommand
Helmhelm repo add kubeshark https://helm.kubeshark.com && helm install kubeshark kubeshark/kubeshark
Homebrewbrew install kubeshark && kubeshark tap
BinaryDownload

Installation guide →


Contributing

We welcome contributions. See CONTRIBUTING.md.

License

Apache-2.0

Topics
cloud-nativedevopsdockerebpfgolanggrpcincident-responsekubernetesmcpnetwork-analysisnetwork-engineeringnetwork-observabilitynetwork-securityobservabilitypcaprestroot-cause-analysissniffersrewireshark
Preguntas frecuentes

Lo que la gente pregunta sobre kubeshark

¿Qué es kubeshark/kubeshark?

kubeshark/kubeshark es subagents para el ecosistema de Claude AI. eBPF-powered network observability for Kubernetes. Indexes L4/L7 traffic with full K8s context, decrypts TLS without keys. Queryable by AI agents via MCP and humans via dashboard. Tiene 12.1k estrellas en GitHub y su última actualización registrada es del 2026-10-21.

¿Cómo se instala kubeshark?

Puedes instalar kubeshark clonando el repositorio (https://github.com/kubeshark/kubeshark) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar kubeshark/kubeshark?

Nuestro agente de seguridad ha analizado kubeshark/kubeshark y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene kubeshark/kubeshark?

kubeshark/kubeshark es mantenido por kubeshark. La última actividad registrada en GitHub es del 2026-10-21, con 141 issues abiertos.

¿Hay alternativas a kubeshark?

Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.

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