Metoro Kubernetes Observability
This MCP server, developed by Metoro, enables AI assistants like Claude to interact with Kubernetes clusters through Metoro's observability platform. Built in Go, it exposes Metoro's APIs to allow querying and analyzing telemetry data collected from microservices using eBPF instrumentation. The implementation stands out by providing deep visibility into Kubernetes environments without requiring code changes. By connecting AI capabilities with Metoro's comprehensive cluster insights, this server enables AI systems to troubleshoot issues, optimize performance, and understand complex microservice interactions. It is particularly useful for DevOps teams seeking to leverage AI for Kubernetes observability, automated incident response, and performance optimization in cloud-native environments.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- cloud-infra
- Source
- PulseMCP
- Repository
- github.com/metoro-io/metoro-mcp-server
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve Metoro Kubernetes Observability from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.