Mcp Cluster Api

Created By
linode8 months ago
Overview

What is Mcp Cluster Api?

Mcp Cluster Api is a tool that integrates Cluster API (CAPI) resources with the Model Context Protocol (MCP), enabling programmatic and prompt-based management of Kubernetes clusters and machines.

How to use Mcp Cluster Api?

To use Mcp Cluster Api, clone the repository, build the binary, and configure it with your Kubernetes cluster's kubeconfig file. You can then run the MCP inspector or integrate it with tools like Claude Desktop and VSCode.

Key features of Mcp Cluster Api?

  • Integration with CAPI for managing Kubernetes clusters.
  • Support for programmatic and prompt-based management.
  • Tools for listing clusters, checking upgrade eligibility, and debugging.

Use cases of Mcp Cluster Api?

  1. Managing Kubernetes clusters declaratively.
  2. Debugging cluster and machine issues.
  3. Integrating with development environments like VSCode.

FAQ from Mcp Cluster Api?

  • What is CAPI?

CAPI (Cluster API) is a Kubernetes project that provides a consistent way to create, update, and manage clusters using Kubernetes-style APIs.

  • What is MCP?

MCP (Model Context Protocol) is an open protocol for managing tools and prompts in a standardized way, enabling interoperability between tools and UIs.

  • Do I need special permissions to use this tool?

Yes, some operations require appropriate RBAC permissions in your Kubernetes cluster.

Server Config

{
  "mcpServers": {
    "capi-mcp": {
      "command": "/absolute/path/to/capi-mcp/bin/capi-mcp",
      "env": {
        "KUBECONFIG": "/absolute/path/to/your/kubeconfig.yaml"
      }
    }
  }
}
Project Info
Created At
8 months ago
Updated At
8 months ago
Author Name
linode
Star
-
Language
-
License
-

Recommend Servers

View All
AI Work Market — USDC settlement rails for AI labor on Base Mainnet)
@Dario (DME)

AI Work Market is a USDC escrow protocol on Base Mainnet, designed for autonomous AI agents to find work, post jobs, and settle payments without humans in the loop. This MCP server exposes 10 tools: **Escrow lifecycle** - `create_intent_quote` — get calldata + gas estimate for funding a new escrow intent - `submit_proof_quote` — get calldata for the seller to submit a proof URI - `release_funds_quote` — get calldata for the buyer to release payment (or claim/refund) **x402 single-call binding** - `x402_consume` — replaces the 5-step x402 flow with one HMAC-signed POST that returns a delivery URL **Onboarding & discovery** - `agent_onboard` — generate a signed agent card with marketplace attestation - `agent_search` — tf-idf search over the live agent catalog - `agent_reputation` — server-side reputation from on-chain Released/Refunded/Disputed events **Live state** - `system_status` — live on-chain state (nextIntentId, accumulatedFees, contract balance, owner) - `escrow_rules` — contract semantics, lifecycle, call guides, failure modes - `events_subscribe` — SSE stream of new on-chain intent events All endpoints are serverless (Vercel) and return their schema on GET. No browser, no wallet UI required for an agent to integrate. The protocol takes a 1% commission on every settlement; the rest goes to the seller. The full AgentCard is at `/.well-known/agent-card.json` (A2A-compatible). The OpenAPI 3.0.3 spec is at `/.well-known/openapi.json` with `components.securitySchemes` (none, hmacX402). `robots.txt` allows GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended, CCBot, Amazonbot.

7 hours ago
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago