io.github.kubeshark/mcp

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by kubeshark

Kubeshark MCP 是实时监控 Kubernetes 网络流量和 API 分析的工具,支持 HTTP、gRPC、Redis、Kafka 和 DNS。

这个服务器解决了在复杂微服务环境中调试网络问题的痛点,适合运维工程师和开发者在生产环境快速定位 API 调用失败或延迟问题。不过,它需要 Kubernetes 集群权限,对新手可能有点门槛。

11.9kGitHub

什么是 io.github.kubeshark/mcp

Kubeshark MCP 是实时监控 Kubernetes 网络流量和 API 分析的工具,支持 HTTP、gRPC、Redis、Kafka 和 DNS。

README

<p align="center"> <img src="https://raw.githubusercontent.com/kubeshark/assets/master/svg/kubeshark-logo.svg" alt="Kubeshark" height="120px"/> </p> <p align="center"> <a href="https://github.com/kubeshark/kubeshark/releases/latest"><img alt="Release" src="https://img.shields.io/github/v/release/kubeshark/kubeshark?logo=GitHub&style=flat-square"></a> <a href="https://hub.docker.com/r/kubeshark/worker"><img alt="Docker pulls" src="https://img.shields.io/docker/pulls/kubeshark/worker?color=%23099cec&logo=Docker&style=flat-square"></a> <a href="https://discord.gg/WkvRGMUcx7"><img alt="Discord" src="https://img.shields.io/discord/1042559155224973352?logo=Discord&style=flat-square&label=discord"></a> <a href="https://join.slack.com/t/kubeshark/shared_invite/zt-3jdcdgxdv-1qNkhBh9c6CFoE7bSPkpBQ"><img alt="Slack" src="https://img.shields.io/badge/slack-join_chat-green?logo=Slack&style=flat-square"></a> </p> <p align="center"><b>Network Observability for SREs & AI Agents</b></p> <p align="center"> <a href="https://demo.kubeshark.com/">Live Demo</a> · <a href="https://docs.kubeshark.com">Docs</a> </p>

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

bash
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:

bash
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:

code
/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

常见问题

io.github.kubeshark/mcp 是什么?

Real-time Kubernetes network traffic visibility and API analysis for HTTP, gRPC, Redis, Kafka, DNS.

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