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

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
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.

Open-source, reusable skills that teach AI agents domain-specific workflows on top of Kubeshark's MCP tools:
| Skill | Description |
|---|---|
| Network RCA | Retrospective root cause analysis — snapshots, dissection, PCAP extraction, trend comparison |
| KFL | KFL (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.
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 →
A visual map of how workloads communicate, showing dependencies, traffic volume, and protocol usage across the cluster.

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 →
| Feature | Description |
|---|---|
| Traffic Snapshots | Point-in-time snapshots with cloud storage (S3, Azure Blob, GCS), PCAP export for Wireshark |
| Traffic Indexing | Real-time and delayed L7 indexing with request/response matching and full payloads |
| Protocol Support | HTTP, gRPC, GraphQL, Redis, Kafka, DNS, and more |
| TLS Decryption | eBPF-based decryption without key management, included in snapshots |
| AI Integration | MCP server + open-source AI skills for network RCA and traffic filtering |
| KFL Query Language | CEL-based query language with Kubernetes, API, and network semantics |
| 100% On-Premises | Air-gapped support, no external dependencies |
| Method | Command |
|---|---|
| Helm | helm repo add kubeshark https://helm.kubeshark.com && helm install kubeshark kubeshark/kubeshark |
| Homebrew | brew install kubeshark && kubeshark tap |
| Binary | Download |
We welcome contributions. See CONTRIBUTING.md.
This listing does not have a supported local package template. Use the maintainer’s documentation for its hosted endpoint, authentication, and client-specific setup. No install command has been inferred.
https://github.com/kubeshark/kubeshark/releases/download/v53.6.0/kubeshark-mcp_darwin_arm64.mcpbotherio.github.kubeshark/mcp works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.