silenceper/mcp-k8s

Description and use

**Brief summary (2‑3 sentences)**
silenceper/mcp-k8s is an open‑source Go server that implements the Model Control Protocol (MCP) on top of Kubernetes, exposing cluster resources via a standard MCP API/SDK/CLI. It lets AI assistants and other MCP‑compatible tools interact with real Kubernetes workloads, making it easy to plug AI‑driven automation into existing DevOps pipelines. With active maintenance, 146 ⭐ on GitHub and recent updates, it is ready for pilot‑grade production use.

**Value**

• **Standardised AI‑to‑infrastructure bridge** – By speaking MCP, the server abstracts away Kubernetes‑specific details, allowing any MCP‑compatible AI agent to discover, query, and act on cluster resources without custom code.
• **Accelerates AI‑enabled tooling** – Teams can quickly prototype AI‑driven operators, self‑healing bots, or data‑pipeline assistants by reusing the same MCP interface across cloud providers and on‑prem clusters.
• **Reusable component** – The server can be deployed as a microservice, exposing both an HTTP API and a Go SDK, which downstream tools can consume directly, reducing duplicated integration effort.

**Practical adoption path**

1. **Deploy the MCP server** in a namespace of the target cluster (Helm chart or plain manifest).
2. **Configure authentication** (RBAC, service‑account token, or OIDC) so that the server can act on behalf of AI agents.
3. **Connect your AI assistant** (or any MCP client) using the provided Go SDK, CLI, or OpenAPI spec; the client can now list pods, watch events, or trigger custom resources via MCP calls.
4. **Iterate** by adding custom MCP extensions or handlers for domain‑specific resources, then promote the setup from a sandbox to staging and finally production.

**Production readiness**

• **Activity & community** – 146 stars, 28 forks, recent commit (2026‑06‑23), and ongoing issue responses indicate an active maintainer base.
• **Maturity** – The project follows semantic versioning, includes CI pipelines, and ships pre‑built Docker images, making deployment repeatable.
• **Security & licensing** – No immediate metadata risks are flagged, but a final review of the OSS license (MIT/Apache‑style) and a vulnerability scan of the container image are recommended before full rollout.
• **Scalability** – Built in Go, it can handle high request rates and can be horizontally scaled behind a Service or Ingress.

Overall, silenceper/mcp-k8s offers a production‑grade, standards‑based entry point for integrating AI assistants with Kubernetes, with a clear, low‑friction path from evaluation to production deployment.

Use in a workflow

silenceper/mcp-k8s helps connect AI assistants to real tools and data through a standard protocol.

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Limitations and review notes

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.